Face Generation

In this project, you'll use generative adversarial networks to generate new images of faces.

Get the Data

You'll be using two datasets in this project:

  • MNIST
  • CelebA

Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.

If you're using FloydHub, set data_dir to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".

In [1]:
data_dir = '/data'
!pip install matplotlib==2.0.2
# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'


"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper

helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
Requirement already satisfied: matplotlib==2.0.2 in /opt/conda/lib/python3.6/site-packages
Requirement already satisfied: numpy>=1.7.1 in /opt/conda/lib/python3.6/site-packages (from matplotlib==2.0.2)
Requirement already satisfied: six>=1.10 in /opt/conda/lib/python3.6/site-packages (from matplotlib==2.0.2)
Requirement already satisfied: python-dateutil in /opt/conda/lib/python3.6/site-packages (from matplotlib==2.0.2)
Requirement already satisfied: pyparsing!=2.0.0,!=2.0.4,!=2.1.2,!=2.1.6,>=1.5.6 in /opt/conda/lib/python3.6/site-packages (from matplotlib==2.0.2)
Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.6/site-packages/cycler-0.10.0-py3.6.egg (from matplotlib==2.0.2)
Requirement already satisfied: pytz in /opt/conda/lib/python3.6/site-packages (from matplotlib==2.0.2)
You are using pip version 9.0.1, however version 18.1 is available.
You should consider upgrading via the 'pip install --upgrade pip' command.
Found mnist Data
Found celeba Data

Explore the Data

MNIST

As you're aware, the MNIST dataset contains images of handwritten digits. You can view the first number of examples by changing show_n_images.

In [2]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot

mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
Out[2]:
<matplotlib.image.AxesImage at 0x7fbbbad060b8>

CelebA

The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images.

In [3]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Out[3]:
<matplotlib.image.AxesImage at 0x7fbbbac28400>

Preprocess the Data

Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

The MNIST images are black and white images with a single color channel while the CelebA images have 3 color channels (RGB color channel).

Build the Neural Network

You'll build the components necessary to build a GANs by implementing the following functions below:

  • model_inputs
  • discriminator
  • generator
  • model_loss
  • model_opt
  • train

Check the Version of TensorFlow and Access to GPU

This will check to make sure you have the correct version of TensorFlow and access to a GPU

In [4]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf

# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer.  You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))

# Check for a GPU
if not tf.test.gpu_device_name():
    warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
    print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
TensorFlow Version: 1.3.0
Default GPU Device: /gpu:0

Input

Implement the model_inputs function to create TF Placeholders for the Neural Network. It should create the following placeholders:

  • Real input images placeholder with rank 4 using image_width, image_height, and image_channels.
  • Z input placeholder with rank 2 using z_dim.
  • Learning rate placeholder with rank 0.

Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)

In [5]:
import problem_unittests as tests

def model_inputs(image_width, image_height, image_channels, z_dim):
    """
    Create the model inputs
    :param image_width: The input image width
    :param image_height: The input image height
    :param image_channels: The number of image channels
    :param z_dim: The dimension of Z
    :return: Tuple of (tensor of real input images, tensor of z data, learning rate)
    """
    # TODO: Implement Function

    real_input_images = tf.placeholder(tf.float32, (None, image_width, image_height, image_channels), name='real_input')
    z_input = tf.placeholder(tf.float32, (None, z_dim), name='z_input')
    learning_rate = tf.placeholder(tf.float32, name='learning_rate')
    
    return real_input_images, z_input, learning_rate


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
ERROR:tensorflow:==================================
Object was never used (type <class 'tensorflow.python.framework.ops.Operation'>):
<tf.Operation 'assert_rank_2/Assert/Assert' type=Assert>
If you want to mark it as used call its "mark_used()" method.
It was originally created here:
['File "/opt/conda/lib/python3.6/runpy.py", line 193, in _run_module_as_main\n    "__main__", mod_spec)', 'File "/opt/conda/lib/python3.6/runpy.py", line 85, in _run_code\n    exec(code, run_globals)', 'File "/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py", line 16, in <module>\n    app.launch_new_instance()', 'File "/opt/conda/lib/python3.6/site-packages/traitlets/config/application.py", line 658, in launch_instance\n    app.start()', 'File "/opt/conda/lib/python3.6/site-packages/ipykernel/kernelapp.py", line 497, in start\n    self.io_loop.start()', 'File "/opt/conda/lib/python3.6/site-packages/tornado/ioloop.py", line 888, in start\n    handler_func(fd_obj, events)', 'File "/opt/conda/lib/python3.6/site-packages/tornado/stack_context.py", line 277, in null_wrapper\n    return fn(*args, **kwargs)', 'File "/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 450, in _handle_events\n    self._handle_recv()', 'File "/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 480, in _handle_recv\n    self._run_callback(callback, msg)', 'File "/opt/conda/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 432, in _run_callback\n    callback(*args, **kwargs)', 'File "/opt/conda/lib/python3.6/site-packages/tornado/stack_context.py", line 277, in null_wrapper\n    return fn(*args, **kwargs)', 'File "/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 283, in dispatcher\n    return self.dispatch_shell(stream, msg)', 'File "/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 233, in dispatch_shell\n    handler(stream, idents, msg)', 'File "/opt/conda/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 399, in execute_request\n    user_expressions, allow_stdin)', 'File "/opt/conda/lib/python3.6/site-packages/ipykernel/ipkernel.py", line 208, in do_execute\n    res = shell.run_cell(code, store_history=store_history, silent=silent)', 'File "/opt/conda/lib/python3.6/site-packages/ipykernel/zmqshell.py", line 537, in run_cell\n    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)', 'File "/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2662, in run_cell\n    raw_cell, store_history, silent, shell_futures)', 'File "/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2785, in _run_cell\n    interactivity=interactivity, compiler=compiler, result=result)', 'File "/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2907, in run_ast_nodes\n    if self.run_code(code, result):', 'File "/opt/conda/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2961, in run_code\n    exec(code_obj, self.user_global_ns, self.user_ns)', 'File "<ipython-input-5-044b864c0d22>", line 24, in <module>\n    tests.test_model_inputs(model_inputs)', 'File "/home/workspace/face_generation/problem_unittests.py", line 12, in func_wrapper\n    result = func(*args)', 'File "/home/workspace/face_generation/problem_unittests.py", line 68, in test_model_inputs\n    _check_input(learn_rate, [], \'Learning Rate\')', 'File "/home/workspace/face_generation/problem_unittests.py", line 34, in _check_input\n    _assert_tensor_shape(tensor, shape, \'Real Input\')', 'File "/home/workspace/face_generation/problem_unittests.py", line 20, in _assert_tensor_shape\n    assert tf.assert_rank(tensor, len(shape), message=\'{} has wrong rank\'.format(display_name))', 'File "/opt/conda/lib/python3.6/site-packages/tensorflow/python/ops/check_ops.py", line 617, in assert_rank\n    dynamic_condition, data, summarize)', 'File "/opt/conda/lib/python3.6/site-packages/tensorflow/python/ops/check_ops.py", line 571, in _assert_rank_condition\n    return control_flow_ops.Assert(condition, data, summarize=summarize)', 'File "/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_should_use.py", line 175, in wrapped\n    return _add_should_use_warning(fn(*args, **kwargs))', 'File "/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_should_use.py", line 144, in _add_should_use_warning\n    wrapped = TFShouldUseWarningWrapper(x)', 'File "/opt/conda/lib/python3.6/site-packages/tensorflow/python/util/tf_should_use.py", line 101, in __init__\n    stack = [s.strip() for s in traceback.format_stack()]']
==================================
Tests Passed

Discriminator

Implement discriminator to create a discriminator neural network that discriminates on images. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the discriminator, tensor logits of the discriminator).

In [95]:
def discriminator(images, reuse=False, alpha=0.01):
    """
    Create the discriminator network
    :param images: Tensor of input image(s)
    :param reuse: Boolean if the weights should be reused
    :return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
    """
    # TODO: Implement Function
    
    with tf.variable_scope('discriminator', reuse=reuse):
        conv1 = tf.layers.conv2d(images * 2., 64, 5, strides=2, padding='same', \
                                           kernel_initializer=tf.contrib.layers.xavier_initializer())
        conv1 = tf.maximum(alpha * conv1, conv1)
        
        conv2 = tf.layers.conv2d(conv1, 128, 5, strides=2, padding='same', \
                                           kernel_initializer=tf.contrib.layers.xavier_initializer())
        conv2 = tf.layers.batch_normalization(conv2, training=True)
        conv2 = tf.maximum(alpha * conv2, conv2)
        
        conv3 = tf.layers.conv2d(conv2, 256, 5, strides=2, padding='same', \
                                           kernel_initializer=tf.contrib.layers.xavier_initializer())
        conv3 = tf.layers.batch_normalization(conv3, training=True)
        conv3 = tf.maximum(alpha * conv3, conv3)
        
        logits = tf.reshape(conv3, (-1, 4*4*256))
        logits = tf.layers.dense(logits, 1)
        out = tf.sigmoid(logits)

        return out, logits


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Tests Passed

Generator

Implement generator to generate an image using z. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim images.

In [89]:
def generator(z, out_channel_dim, is_train=True, alpha=0.01):
    """
    Create the generator network
    :param z: Input z
    :param out_channel_dim: The number of channels in the output image
    :param is_train: Boolean if generator is being used for training
    :return: The tensor output of the generator
    """
    # TODO: Implement Function
    
    with tf.variable_scope('generator', reuse=not is_train):
        fc = tf.layers.dense(z, 7 * 7 * 512)
        
        fc = tf.reshape(fc, (-1, 7, 7, 512))
        fc = tf.layers.batch_normalization(fc, training=is_train)
        fc = tf.maximum(alpha * fc, fc)
        
        conv1 = tf.layers.conv2d_transpose(fc, 256, 5, strides=2, padding='same', \
                                           kernel_initializer=tf.contrib.layers.xavier_initializer())
        conv1 = tf.layers.batch_normalization(conv1, training=is_train)
        conv1 = tf.maximum(alpha * conv1, conv1)
        
        conv2 = tf.layers.conv2d_transpose(conv1, 128, 5, strides=2, padding='same', \
                                           kernel_initializer=tf.contrib.layers.xavier_initializer())
        conv2 = tf.layers.batch_normalization(conv2, training=is_train)
        conv2 = tf.maximum(alpha * conv2, conv2)
        
        logits = tf.layers.conv2d_transpose(conv2, out_channel_dim, 5, strides=1, padding='same', \
                                           kernel_initializer=tf.contrib.layers.xavier_initializer())
        out = tf.tanh(logits)
        
        return out


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Tests Passed

Loss

Implement model_loss to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:

  • discriminator(images, reuse=False)
  • generator(z, out_channel_dim, is_train=True)
In [90]:
def model_loss(input_real, input_z, out_channel_dim, smooth=0.1):
    """
    Get the loss for the discriminator and generator
    :param input_real: Images from the real dataset
    :param input_z: Z input
    :param out_channel_dim: The number of channels in the output image
    :return: A tuple of (discriminator loss, generator loss)
    """
    # TODO: Implement Function
    
    g_model = generator(input_z, out_channel_dim)
    d_model_real, d_logits_real = discriminator(input_real)
    d_model_fake, d_logits_fake = discriminator(g_model, reuse=True)
    
    d_loss_real = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real, labels=tf.ones_like(d_model_real) * (1 - smooth)))
    d_loss_fake = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.zeros_like(d_model_fake)))
    g_loss = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.ones_like(d_model_fake)))
    
    d_loss = d_loss_real + d_loss_fake
    
    return d_loss, g_loss


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Tests Passed

Optimization

Implement model_opt to create the optimization operations for the GANs. Use tf.trainable_variables to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).

In [91]:
def model_opt(d_loss, g_loss, learning_rate, beta1):
    """
    Get optimization operations
    :param d_loss: Discriminator loss Tensor
    :param g_loss: Generator loss Tensor
    :param learning_rate: Learning Rate Placeholder
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :return: A tuple of (discriminator training operation, generator training operation)
    """
    # TODO: Implement Function
    
    t_vars = tf.trainable_variables()
    d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
    g_vars = [var for var in t_vars if var.name.startswith('generator')]
    
    with tf.control_dependencies(tf.get_collection(tf.GraphKeys.UPDATE_OPS)):
        d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(d_loss, var_list=d_vars)
        g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(g_loss, var_list=g_vars)
    
    return d_train_opt, g_train_opt


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
Tests Passed

Neural Network Training

Show Output

Use this function to show the current output of the generator during training. It will help you determine how well the GANs is training.

In [92]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np

def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
    """
    Show example output for the generator
    :param sess: TensorFlow session
    :param n_images: Number of Images to display
    :param input_z: Input Z Tensor
    :param out_channel_dim: The number of channels in the output image
    :param image_mode: The mode to use for images ("RGB" or "L")
    """
    cmap = None if image_mode == 'RGB' else 'gray'
    z_dim = input_z.get_shape().as_list()[-1]
    example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])

    samples = sess.run(
        generator(input_z, out_channel_dim, False),
        feed_dict={input_z: example_z})

    images_grid = helper.images_square_grid(samples, image_mode)
    pyplot.imshow(images_grid, cmap=cmap)
    pyplot.show()

Train

Implement train to build and train the GANs. Use the following functions you implemented:

  • model_inputs(image_width, image_height, image_channels, z_dim)
  • model_loss(input_real, input_z, out_channel_dim)
  • model_opt(d_loss, g_loss, learning_rate, beta1)

Use the show_generator_output to show generator output while you train. Running show_generator_output for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator output every 100 batches.

In [111]:
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
    """
    Train the GAN
    :param epoch_count: Number of epochs
    :param batch_size: Batch Size
    :param z_dim: Z dimension
    :param learning_rate: Learning Rate
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :param get_batches: Function to get batches
    :param data_shape: Shape of the data
    :param data_image_mode: The image mode to use for images ("RGB" or "L")
    """
    # TODO: Build Model
    
    input_real, input_z, lr = model_inputs(data_shape[1], data_shape[2], data_shape[3], z_dim)
    d_loss, g_loss = model_loss(input_real, input_z, data_shape[3])
    d_opt, g_opt = model_opt(d_loss, g_loss, lr, beta1)
    
    iterations = 0
    
    with tf.Session() as sess:
        sess.run(tf.global_variables_initializer())
        for epoch_i in range(epoch_count):
            for batch_images in get_batches(batch_size):
                # TODO: Train Model
                
                # make sure the inputs range from -1 to 1
                batch_images = batch_images * 2
                
                iterations += 1
                
                batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))
                
                _ = sess.run(d_opt, feed_dict={input_real: batch_images, input_z: batch_z, lr: learning_rate})
                _ = sess.run(g_opt, feed_dict={input_real: batch_images, input_z: batch_z, lr: learning_rate})
                
                if iterations % 10 == 0:
                    train_loss_d = d_loss.eval({input_z: batch_z, input_real: batch_images})
                    train_loss_g = g_loss.eval({input_z: batch_z})
                    
                    print('Epoch {} out of {}'.format(epoch_i + 1, epochs))
                    print('Iteration {}'.format(iterations))
                    print('Discriminator loss: {:.6f}'.format(train_loss_d))
                    print('Generator loss: {:.6f}'.format(train_loss_g))
                    print('=' * 15)
                
                if iterations % 100 == 0:
                    show_generator_output(sess, 16, input_z, data_shape[3], data_image_mode)
                

MNIST

Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.

In [112]:
batch_size = 32
z_dim = 100
learning_rate = 0.0002
beta1 = 0.5

"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2

mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))

with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
          mnist_dataset.shape, mnist_dataset.image_mode)
Epoch 1 out of 2
Iteration 10
Discriminator loss: 0.465071
Generator loss: 2.542798
===============
Epoch 1 out of 2
Iteration 20
Discriminator loss: 0.704013
Generator loss: 1.374265
===============
Epoch 1 out of 2
Iteration 30
Discriminator loss: 1.579813
Generator loss: 4.614997
===============
Epoch 1 out of 2
Iteration 40
Discriminator loss: 0.779875
Generator loss: 1.811049
===============
Epoch 1 out of 2
Iteration 50
Discriminator loss: 1.514522
Generator loss: 0.752426
===============
Epoch 1 out of 2
Iteration 60
Discriminator loss: 0.849975
Generator loss: 1.489880
===============
Epoch 1 out of 2
Iteration 70
Discriminator loss: 0.897599
Generator loss: 1.452857
===============
Epoch 1 out of 2
Iteration 80
Discriminator loss: 0.931503
Generator loss: 1.523070
===============
Epoch 1 out of 2
Iteration 90
Discriminator loss: 0.950457
Generator loss: 1.294697
===============
Epoch 1 out of 2
Iteration 100
Discriminator loss: 1.389392
Generator loss: 0.945542
===============
Epoch 1 out of 2
Iteration 110
Discriminator loss: 1.497258
Generator loss: 0.569606
===============
Epoch 1 out of 2
Iteration 120
Discriminator loss: 1.487552
Generator loss: 0.621812
===============
Epoch 1 out of 2
Iteration 130
Discriminator loss: 1.705839
Generator loss: 0.412245
===============
Epoch 1 out of 2
Iteration 140
Discriminator loss: 1.255168
Generator loss: 1.058099
===============
Epoch 1 out of 2
Iteration 150
Discriminator loss: 1.470637
Generator loss: 0.582340
===============
Epoch 1 out of 2
Iteration 160
Discriminator loss: 1.648017
Generator loss: 0.393959
===============
Epoch 1 out of 2
Iteration 170
Discriminator loss: 1.188754
Generator loss: 0.812806
===============
Epoch 1 out of 2
Iteration 180
Discriminator loss: 1.275961
Generator loss: 1.486717
===============
Epoch 1 out of 2
Iteration 190
Discriminator loss: 1.333701
Generator loss: 0.663761
===============
Epoch 1 out of 2
Iteration 200
Discriminator loss: 1.336006
Generator loss: 0.700888
===============
Epoch 1 out of 2
Iteration 210
Discriminator loss: 1.090556
Generator loss: 1.204594
===============
Epoch 1 out of 2
Iteration 220
Discriminator loss: 1.245241
Generator loss: 0.887319
===============
Epoch 1 out of 2
Iteration 230
Discriminator loss: 1.260391
Generator loss: 0.629995
===============
Epoch 1 out of 2
Iteration 240
Discriminator loss: 1.393232
Generator loss: 0.551101
===============
Epoch 1 out of 2
Iteration 250
Discriminator loss: 1.137237
Generator loss: 0.791477
===============
Epoch 1 out of 2
Iteration 260
Discriminator loss: 1.607456
Generator loss: 0.398675
===============
Epoch 1 out of 2
Iteration 270
Discriminator loss: 1.163598
Generator loss: 1.756295
===============
Epoch 1 out of 2
Iteration 280
Discriminator loss: 1.070777
Generator loss: 0.984961
===============
Epoch 1 out of 2
Iteration 290
Discriminator loss: 1.127469
Generator loss: 0.950086
===============
Epoch 1 out of 2
Iteration 300
Discriminator loss: 1.435872
Generator loss: 0.567557
===============
Epoch 1 out of 2
Iteration 310
Discriminator loss: 1.314590
Generator loss: 0.609157
===============
Epoch 1 out of 2
Iteration 320
Discriminator loss: 1.437346
Generator loss: 0.552470
===============
Epoch 1 out of 2
Iteration 330
Discriminator loss: 1.223301
Generator loss: 0.646913
===============
Epoch 1 out of 2
Iteration 340
Discriminator loss: 1.513983
Generator loss: 0.439104
===============
Epoch 1 out of 2
Iteration 350
Discriminator loss: 1.118584
Generator loss: 0.830513
===============
Epoch 1 out of 2
Iteration 360
Discriminator loss: 1.337615
Generator loss: 1.595385
===============
Epoch 1 out of 2
Iteration 370
Discriminator loss: 1.092085
Generator loss: 0.923168
===============
Epoch 1 out of 2
Iteration 380
Discriminator loss: 1.571278
Generator loss: 0.428429
===============
Epoch 1 out of 2
Iteration 390
Discriminator loss: 1.084697
Generator loss: 0.932614
===============
Epoch 1 out of 2
Iteration 400
Discriminator loss: 1.390145
Generator loss: 0.670565
===============
Epoch 1 out of 2
Iteration 410
Discriminator loss: 1.180789
Generator loss: 1.343949
===============
Epoch 1 out of 2
Iteration 420
Discriminator loss: 1.341706
Generator loss: 0.544913
===============
Epoch 1 out of 2
Iteration 430
Discriminator loss: 1.290221
Generator loss: 0.669417
===============
Epoch 1 out of 2
Iteration 440
Discriminator loss: 1.398247
Generator loss: 0.616245
===============
Epoch 1 out of 2
Iteration 450
Discriminator loss: 1.609025
Generator loss: 0.383174
===============
Epoch 1 out of 2
Iteration 460
Discriminator loss: 1.303294
Generator loss: 1.733896
===============
Epoch 1 out of 2
Iteration 470
Discriminator loss: 1.543713
Generator loss: 0.449266
===============
Epoch 1 out of 2
Iteration 480
Discriminator loss: 1.123936
Generator loss: 1.066205
===============
Epoch 1 out of 2
Iteration 490
Discriminator loss: 1.321121
Generator loss: 0.571870
===============
Epoch 1 out of 2
Iteration 500
Discriminator loss: 1.334091
Generator loss: 1.933881
===============
Epoch 1 out of 2
Iteration 510
Discriminator loss: 1.197298
Generator loss: 0.700449
===============
Epoch 1 out of 2
Iteration 520
Discriminator loss: 1.210359
Generator loss: 0.881790
===============
Epoch 1 out of 2
Iteration 530
Discriminator loss: 1.252791
Generator loss: 0.768964
===============
Epoch 1 out of 2
Iteration 540
Discriminator loss: 1.109878
Generator loss: 0.942142
===============
Epoch 1 out of 2
Iteration 550
Discriminator loss: 1.294966
Generator loss: 0.590219
===============
Epoch 1 out of 2
Iteration 560
Discriminator loss: 0.969917
Generator loss: 1.027413
===============
Epoch 1 out of 2
Iteration 570
Discriminator loss: 1.057864
Generator loss: 1.042237
===============
Epoch 1 out of 2
Iteration 580
Discriminator loss: 1.159806
Generator loss: 0.890396
===============
Epoch 1 out of 2
Iteration 590
Discriminator loss: 1.162635
Generator loss: 1.500123
===============
Epoch 1 out of 2
Iteration 600
Discriminator loss: 1.041266
Generator loss: 0.962613
===============
Epoch 1 out of 2
Iteration 610
Discriminator loss: 1.065228
Generator loss: 0.955633
===============
Epoch 1 out of 2
Iteration 620
Discriminator loss: 1.436851
Generator loss: 0.541390
===============
Epoch 1 out of 2
Iteration 630
Discriminator loss: 1.075888
Generator loss: 0.840837
===============
Epoch 1 out of 2
Iteration 640
Discriminator loss: 1.704481
Generator loss: 0.329941
===============
Epoch 1 out of 2
Iteration 650
Discriminator loss: 1.165303
Generator loss: 0.797697
===============
Epoch 1 out of 2
Iteration 660
Discriminator loss: 1.276818
Generator loss: 0.730118
===============
Epoch 1 out of 2
Iteration 670
Discriminator loss: 1.333717
Generator loss: 0.539140
===============
Epoch 1 out of 2
Iteration 680
Discriminator loss: 1.132987
Generator loss: 1.634639
===============
Epoch 1 out of 2
Iteration 690
Discriminator loss: 1.377163
Generator loss: 0.559341
===============
Epoch 1 out of 2
Iteration 700
Discriminator loss: 1.140125
Generator loss: 0.794183
===============
Epoch 1 out of 2
Iteration 710
Discriminator loss: 0.953565
Generator loss: 1.015405
===============
Epoch 1 out of 2
Iteration 720
Discriminator loss: 1.143090
Generator loss: 1.131126
===============
Epoch 1 out of 2
Iteration 730
Discriminator loss: 1.152717
Generator loss: 0.692596
===============
Epoch 1 out of 2
Iteration 740
Discriminator loss: 1.145161
Generator loss: 0.834124
===============
Epoch 1 out of 2
Iteration 750
Discriminator loss: 1.005765
Generator loss: 1.189608
===============
Epoch 1 out of 2
Iteration 760
Discriminator loss: 1.090784
Generator loss: 0.991983
===============
Epoch 1 out of 2
Iteration 770
Discriminator loss: 1.010318
Generator loss: 0.890074
===============
Epoch 1 out of 2
Iteration 780
Discriminator loss: 0.912063
Generator loss: 1.359660
===============
Epoch 1 out of 2
Iteration 790
Discriminator loss: 1.094685
Generator loss: 0.867064
===============
Epoch 1 out of 2
Iteration 800
Discriminator loss: 1.069805
Generator loss: 0.954641
===============
Epoch 1 out of 2
Iteration 810
Discriminator loss: 1.051960
Generator loss: 0.840826
===============
Epoch 1 out of 2
Iteration 820
Discriminator loss: 1.208291
Generator loss: 0.698579
===============
Epoch 1 out of 2
Iteration 830
Discriminator loss: 1.084867
Generator loss: 1.174082
===============
Epoch 1 out of 2
Iteration 840
Discriminator loss: 1.399607
Generator loss: 0.564262
===============
Epoch 1 out of 2
Iteration 850
Discriminator loss: 1.235157
Generator loss: 0.733906
===============
Epoch 1 out of 2
Iteration 860
Discriminator loss: 0.917890
Generator loss: 1.770173
===============
Epoch 1 out of 2
Iteration 870
Discriminator loss: 0.946326
Generator loss: 1.107808
===============
Epoch 1 out of 2
Iteration 880
Discriminator loss: 1.076055
Generator loss: 1.035229
===============
Epoch 1 out of 2
Iteration 890
Discriminator loss: 1.318517
Generator loss: 0.594692
===============
Epoch 1 out of 2
Iteration 900
Discriminator loss: 1.087165
Generator loss: 1.379673
===============
Epoch 1 out of 2
Iteration 910
Discriminator loss: 1.367184
Generator loss: 0.507364
===============
Epoch 1 out of 2
Iteration 920
Discriminator loss: 1.184050
Generator loss: 0.776691
===============
Epoch 1 out of 2
Iteration 930
Discriminator loss: 1.566941
Generator loss: 0.414663
===============
Epoch 1 out of 2
Iteration 940
Discriminator loss: 1.588472
Generator loss: 0.438823
===============
Epoch 1 out of 2
Iteration 950
Discriminator loss: 1.217995
Generator loss: 0.856211
===============
Epoch 1 out of 2
Iteration 960
Discriminator loss: 1.276053
Generator loss: 0.602350
===============
Epoch 1 out of 2
Iteration 970
Discriminator loss: 1.093568
Generator loss: 0.839113
===============
Epoch 1 out of 2
Iteration 980
Discriminator loss: 1.095126
Generator loss: 0.775632
===============
Epoch 1 out of 2
Iteration 990
Discriminator loss: 1.854681
Generator loss: 0.290383
===============
Epoch 1 out of 2
Iteration 1000
Discriminator loss: 1.099707
Generator loss: 0.922658
===============
Epoch 1 out of 2
Iteration 1010
Discriminator loss: 0.937092
Generator loss: 1.038390
===============
Epoch 1 out of 2
Iteration 1020
Discriminator loss: 1.161144
Generator loss: 0.719416
===============
Epoch 1 out of 2
Iteration 1030
Discriminator loss: 1.130294
Generator loss: 1.002254
===============
Epoch 1 out of 2
Iteration 1040
Discriminator loss: 0.995444
Generator loss: 1.611441
===============
Epoch 1 out of 2
Iteration 1050
Discriminator loss: 1.109756
Generator loss: 0.798539
===============
Epoch 1 out of 2
Iteration 1060
Discriminator loss: 1.160172
Generator loss: 0.684765
===============
Epoch 1 out of 2
Iteration 1070
Discriminator loss: 0.891261
Generator loss: 1.519273
===============
Epoch 1 out of 2
Iteration 1080
Discriminator loss: 1.157516
Generator loss: 0.921274
===============
Epoch 1 out of 2
Iteration 1090
Discriminator loss: 1.029771
Generator loss: 0.989937
===============
Epoch 1 out of 2
Iteration 1100
Discriminator loss: 1.321339
Generator loss: 0.544294
===============
Epoch 1 out of 2
Iteration 1110
Discriminator loss: 1.285130
Generator loss: 0.604971
===============
Epoch 1 out of 2
Iteration 1120
Discriminator loss: 1.046016
Generator loss: 0.827164
===============
Epoch 1 out of 2
Iteration 1130
Discriminator loss: 0.842631
Generator loss: 1.398589
===============
Epoch 1 out of 2
Iteration 1140
Discriminator loss: 1.312928
Generator loss: 0.559473
===============
Epoch 1 out of 2
Iteration 1150
Discriminator loss: 0.898736
Generator loss: 1.338554
===============
Epoch 1 out of 2
Iteration 1160
Discriminator loss: 1.180495
Generator loss: 0.804850
===============
Epoch 1 out of 2
Iteration 1170
Discriminator loss: 1.045111
Generator loss: 0.992336
===============
Epoch 1 out of 2
Iteration 1180
Discriminator loss: 0.918549
Generator loss: 1.014155
===============
Epoch 1 out of 2
Iteration 1190
Discriminator loss: 1.047557
Generator loss: 0.890895
===============
Epoch 1 out of 2
Iteration 1200
Discriminator loss: 0.974786
Generator loss: 0.906234
===============
Epoch 1 out of 2
Iteration 1210
Discriminator loss: 1.125788
Generator loss: 1.383531
===============
Epoch 1 out of 2
Iteration 1220
Discriminator loss: 1.016643
Generator loss: 1.033327
===============
Epoch 1 out of 2
Iteration 1230
Discriminator loss: 1.058908
Generator loss: 0.889921
===============
Epoch 1 out of 2
Iteration 1240
Discriminator loss: 1.017455
Generator loss: 0.927350
===============
Epoch 1 out of 2
Iteration 1250
Discriminator loss: 0.992072
Generator loss: 1.011843
===============
Epoch 1 out of 2
Iteration 1260
Discriminator loss: 1.388276
Generator loss: 0.527489
===============
Epoch 1 out of 2
Iteration 1270
Discriminator loss: 1.178220
Generator loss: 1.841991
===============
Epoch 1 out of 2
Iteration 1280
Discriminator loss: 1.177043
Generator loss: 0.685799
===============
Epoch 1 out of 2
Iteration 1290
Discriminator loss: 0.913440
Generator loss: 1.084597
===============
Epoch 1 out of 2
Iteration 1300
Discriminator loss: 0.944662
Generator loss: 0.975550
===============
Epoch 1 out of 2
Iteration 1310
Discriminator loss: 1.152516
Generator loss: 0.809137
===============
Epoch 1 out of 2
Iteration 1320
Discriminator loss: 1.078517
Generator loss: 0.756005
===============
Epoch 1 out of 2
Iteration 1330
Discriminator loss: 1.279686
Generator loss: 0.699313
===============
Epoch 1 out of 2
Iteration 1340
Discriminator loss: 1.193002
Generator loss: 0.848619
===============
Epoch 1 out of 2
Iteration 1350
Discriminator loss: 1.143839
Generator loss: 0.702396
===============
Epoch 1 out of 2
Iteration 1360
Discriminator loss: 1.248748
Generator loss: 0.633288
===============
Epoch 1 out of 2
Iteration 1370
Discriminator loss: 1.047428
Generator loss: 0.918562
===============
Epoch 1 out of 2
Iteration 1380
Discriminator loss: 1.023452
Generator loss: 1.057192
===============
Epoch 1 out of 2
Iteration 1390
Discriminator loss: 0.884504
Generator loss: 1.243505
===============
Epoch 1 out of 2
Iteration 1400
Discriminator loss: 1.245275
Generator loss: 0.630482
===============
Epoch 1 out of 2
Iteration 1410
Discriminator loss: 0.922741
Generator loss: 1.000824
===============
Epoch 1 out of 2
Iteration 1420
Discriminator loss: 1.165232
Generator loss: 1.794171
===============
Epoch 1 out of 2
Iteration 1430
Discriminator loss: 0.965695
Generator loss: 1.204882
===============
Epoch 1 out of 2
Iteration 1440
Discriminator loss: 0.752747
Generator loss: 1.385430
===============
Epoch 1 out of 2
Iteration 1450
Discriminator loss: 1.105217
Generator loss: 0.811175
===============
Epoch 1 out of 2
Iteration 1460
Discriminator loss: 1.296835
Generator loss: 0.590854
===============
Epoch 1 out of 2
Iteration 1470
Discriminator loss: 1.492852
Generator loss: 0.462968
===============
Epoch 1 out of 2
Iteration 1480
Discriminator loss: 1.148917
Generator loss: 0.832923
===============
Epoch 1 out of 2
Iteration 1490
Discriminator loss: 1.081470
Generator loss: 0.747500
===============
Epoch 1 out of 2
Iteration 1500
Discriminator loss: 1.122428
Generator loss: 1.193544
===============
Epoch 1 out of 2
Iteration 1510
Discriminator loss: 0.956760
Generator loss: 1.219528
===============
Epoch 1 out of 2
Iteration 1520
Discriminator loss: 0.976055
Generator loss: 0.870711
===============
Epoch 1 out of 2
Iteration 1530
Discriminator loss: 0.894990
Generator loss: 1.085825
===============
Epoch 1 out of 2
Iteration 1540
Discriminator loss: 1.660050
Generator loss: 0.404424
===============
Epoch 1 out of 2
Iteration 1550
Discriminator loss: 1.044949
Generator loss: 0.882180
===============
Epoch 1 out of 2
Iteration 1560
Discriminator loss: 1.008873
Generator loss: 0.894905
===============
Epoch 1 out of 2
Iteration 1570
Discriminator loss: 1.813136
Generator loss: 0.331047
===============
Epoch 1 out of 2
Iteration 1580
Discriminator loss: 0.789052
Generator loss: 1.307748
===============
Epoch 1 out of 2
Iteration 1590
Discriminator loss: 1.057233
Generator loss: 0.899203
===============
Epoch 1 out of 2
Iteration 1600
Discriminator loss: 0.787265
Generator loss: 1.394845
===============
Epoch 1 out of 2
Iteration 1610
Discriminator loss: 1.027961
Generator loss: 1.300903
===============
Epoch 1 out of 2
Iteration 1620
Discriminator loss: 1.179166
Generator loss: 0.701103
===============
Epoch 1 out of 2
Iteration 1630
Discriminator loss: 0.933243
Generator loss: 1.061711
===============
Epoch 1 out of 2
Iteration 1640
Discriminator loss: 0.815454
Generator loss: 1.263750
===============
Epoch 1 out of 2
Iteration 1650
Discriminator loss: 0.854394
Generator loss: 1.384365
===============
Epoch 1 out of 2
Iteration 1660
Discriminator loss: 1.215353
Generator loss: 0.656040
===============
Epoch 1 out of 2
Iteration 1670
Discriminator loss: 1.682375
Generator loss: 0.395477
===============
Epoch 1 out of 2
Iteration 1680
Discriminator loss: 0.964543
Generator loss: 1.064180
===============
Epoch 1 out of 2
Iteration 1690
Discriminator loss: 0.966910
Generator loss: 1.081014
===============
Epoch 1 out of 2
Iteration 1700
Discriminator loss: 0.962497
Generator loss: 1.009849
===============
Epoch 1 out of 2
Iteration 1710
Discriminator loss: 1.285419
Generator loss: 0.568147
===============
Epoch 1 out of 2
Iteration 1720
Discriminator loss: 1.043864
Generator loss: 0.792317
===============
Epoch 1 out of 2
Iteration 1730
Discriminator loss: 0.896827
Generator loss: 1.085292
===============
Epoch 1 out of 2
Iteration 1740
Discriminator loss: 0.778023
Generator loss: 1.257759
===============
Epoch 1 out of 2
Iteration 1750
Discriminator loss: 1.073960
Generator loss: 1.261114
===============
Epoch 1 out of 2
Iteration 1760
Discriminator loss: 0.689569
Generator loss: 1.715063
===============
Epoch 1 out of 2
Iteration 1770
Discriminator loss: 1.319017
Generator loss: 0.617547
===============
Epoch 1 out of 2
Iteration 1780
Discriminator loss: 1.053676
Generator loss: 0.868992
===============
Epoch 1 out of 2
Iteration 1790
Discriminator loss: 1.187337
Generator loss: 2.649245
===============
Epoch 1 out of 2
Iteration 1800
Discriminator loss: 1.062375
Generator loss: 0.837708
===============
Epoch 1 out of 2
Iteration 1810
Discriminator loss: 1.206765
Generator loss: 0.699187
===============
Epoch 1 out of 2
Iteration 1820
Discriminator loss: 0.903476
Generator loss: 1.130904
===============
Epoch 1 out of 2
Iteration 1830
Discriminator loss: 1.264616
Generator loss: 0.623876
===============
Epoch 1 out of 2
Iteration 1840
Discriminator loss: 1.093524
Generator loss: 0.760733
===============
Epoch 1 out of 2
Iteration 1850
Discriminator loss: 1.186441
Generator loss: 0.704366
===============
Epoch 1 out of 2
Iteration 1860
Discriminator loss: 1.172863
Generator loss: 0.824420
===============
Epoch 1 out of 2
Iteration 1870
Discriminator loss: 1.118494
Generator loss: 0.765131
===============
Epoch 2 out of 2
Iteration 1880
Discriminator loss: 0.901066
Generator loss: 1.030312
===============
Epoch 2 out of 2
Iteration 1890
Discriminator loss: 1.154718
Generator loss: 0.727537
===============
Epoch 2 out of 2
Iteration 1900
Discriminator loss: 1.094364
Generator loss: 0.746941
===============
Epoch 2 out of 2
Iteration 1910
Discriminator loss: 0.745364
Generator loss: 1.431522
===============
Epoch 2 out of 2
Iteration 1920
Discriminator loss: 1.012831
Generator loss: 1.380993
===============
Epoch 2 out of 2
Iteration 1930
Discriminator loss: 1.060606
Generator loss: 0.864230
===============
Epoch 2 out of 2
Iteration 1940
Discriminator loss: 1.045302
Generator loss: 1.622604
===============
Epoch 2 out of 2
Iteration 1950
Discriminator loss: 0.866436
Generator loss: 1.808341
===============
Epoch 2 out of 2
Iteration 1960
Discriminator loss: 0.924626
Generator loss: 0.932887
===============
Epoch 2 out of 2
Iteration 1970
Discriminator loss: 1.051682
Generator loss: 0.901832
===============
Epoch 2 out of 2
Iteration 1980
Discriminator loss: 1.775261
Generator loss: 0.396881
===============
Epoch 2 out of 2
Iteration 1990
Discriminator loss: 1.337501
Generator loss: 0.667907
===============
Epoch 2 out of 2
Iteration 2000
Discriminator loss: 0.962335
Generator loss: 1.102277
===============
Epoch 2 out of 2
Iteration 2010
Discriminator loss: 0.824919
Generator loss: 1.342985
===============
Epoch 2 out of 2
Iteration 2020
Discriminator loss: 0.896431
Generator loss: 1.216467
===============
Epoch 2 out of 2
Iteration 2030
Discriminator loss: 1.133265
Generator loss: 0.743698
===============
Epoch 2 out of 2
Iteration 2040
Discriminator loss: 1.173623
Generator loss: 0.639067
===============
Epoch 2 out of 2
Iteration 2050
Discriminator loss: 1.568414
Generator loss: 0.475841
===============
Epoch 2 out of 2
Iteration 2060
Discriminator loss: 1.090119
Generator loss: 0.782915
===============
Epoch 2 out of 2
Iteration 2070
Discriminator loss: 1.162366
Generator loss: 0.752363
===============
Epoch 2 out of 2
Iteration 2080
Discriminator loss: 0.917097
Generator loss: 1.909173
===============
Epoch 2 out of 2
Iteration 2090
Discriminator loss: 1.227670
Generator loss: 0.663984
===============
Epoch 2 out of 2
Iteration 2100
Discriminator loss: 1.454795
Generator loss: 0.508559
===============
Epoch 2 out of 2
Iteration 2110
Discriminator loss: 0.834312
Generator loss: 1.208994
===============
Epoch 2 out of 2
Iteration 2120
Discriminator loss: 1.283025
Generator loss: 0.641492
===============
Epoch 2 out of 2
Iteration 2130
Discriminator loss: 0.980703
Generator loss: 0.970107
===============
Epoch 2 out of 2
Iteration 2140
Discriminator loss: 1.404336
Generator loss: 0.491091
===============
Epoch 2 out of 2
Iteration 2150
Discriminator loss: 1.026830
Generator loss: 0.829799
===============
Epoch 2 out of 2
Iteration 2160
Discriminator loss: 0.924115
Generator loss: 0.965247
===============
Epoch 2 out of 2
Iteration 2170
Discriminator loss: 1.103681
Generator loss: 0.845384
===============
Epoch 2 out of 2
Iteration 2180
Discriminator loss: 0.998121
Generator loss: 0.820195
===============
Epoch 2 out of 2
Iteration 2190
Discriminator loss: 1.226756
Generator loss: 0.642943
===============
Epoch 2 out of 2
Iteration 2200
Discriminator loss: 0.924951
Generator loss: 1.023691
===============
Epoch 2 out of 2
Iteration 2210
Discriminator loss: 1.094797
Generator loss: 0.865477
===============
Epoch 2 out of 2
Iteration 2220
Discriminator loss: 0.929526
Generator loss: 1.775443
===============
Epoch 2 out of 2
Iteration 2230
Discriminator loss: 1.012480
Generator loss: 0.895263
===============
Epoch 2 out of 2
Iteration 2240
Discriminator loss: 0.976437
Generator loss: 0.948089
===============
Epoch 2 out of 2
Iteration 2250
Discriminator loss: 1.331974
Generator loss: 0.570617
===============
Epoch 2 out of 2
Iteration 2260
Discriminator loss: 0.954874
Generator loss: 1.696032
===============
Epoch 2 out of 2
Iteration 2270
Discriminator loss: 0.785929
Generator loss: 1.284605
===============
Epoch 2 out of 2
Iteration 2280
Discriminator loss: 2.207328
Generator loss: 0.221078
===============
Epoch 2 out of 2
Iteration 2290
Discriminator loss: 0.887699
Generator loss: 1.243402
===============
Epoch 2 out of 2
Iteration 2300
Discriminator loss: 1.167228
Generator loss: 0.691467
===============
Epoch 2 out of 2
Iteration 2310
Discriminator loss: 0.758375
Generator loss: 1.640103
===============
Epoch 2 out of 2
Iteration 2320
Discriminator loss: 1.218435
Generator loss: 0.659675
===============
Epoch 2 out of 2
Iteration 2330
Discriminator loss: 1.413717
Generator loss: 0.527699
===============
Epoch 2 out of 2
Iteration 2340
Discriminator loss: 0.828203
Generator loss: 1.581390
===============
Epoch 2 out of 2
Iteration 2350
Discriminator loss: 0.880716
Generator loss: 1.230871
===============
Epoch 2 out of 2
Iteration 2360
Discriminator loss: 0.976154
Generator loss: 1.005009
===============
Epoch 2 out of 2
Iteration 2370
Discriminator loss: 0.781026
Generator loss: 1.591964
===============
Epoch 2 out of 2
Iteration 2380
Discriminator loss: 0.981122
Generator loss: 1.000006
===============
Epoch 2 out of 2
Iteration 2390
Discriminator loss: 0.890777
Generator loss: 1.041686
===============
Epoch 2 out of 2
Iteration 2400
Discriminator loss: 0.737632
Generator loss: 1.397084
===============
Epoch 2 out of 2
Iteration 2410
Discriminator loss: 1.005025
Generator loss: 1.140912
===============
Epoch 2 out of 2
Iteration 2420
Discriminator loss: 1.298306
Generator loss: 0.587839
===============
Epoch 2 out of 2
Iteration 2430
Discriminator loss: 0.792965
Generator loss: 1.264464
===============
Epoch 2 out of 2
Iteration 2440
Discriminator loss: 1.203229
Generator loss: 0.826473
===============
Epoch 2 out of 2
Iteration 2450
Discriminator loss: 0.892440
Generator loss: 1.094107
===============
Epoch 2 out of 2
Iteration 2460
Discriminator loss: 0.624646
Generator loss: 2.006467
===============
Epoch 2 out of 2
Iteration 2470
Discriminator loss: 0.942489
Generator loss: 0.956620
===============
Epoch 2 out of 2
Iteration 2480
Discriminator loss: 1.364294
Generator loss: 0.560139
===============
Epoch 2 out of 2
Iteration 2490
Discriminator loss: 1.103131
Generator loss: 0.802800
===============
Epoch 2 out of 2
Iteration 2500
Discriminator loss: 0.851676
Generator loss: 1.342998
===============
Epoch 2 out of 2
Iteration 2510
Discriminator loss: 0.831478
Generator loss: 1.521210
===============
Epoch 2 out of 2
Iteration 2520
Discriminator loss: 1.760531
Generator loss: 3.094336
===============
Epoch 2 out of 2
Iteration 2530
Discriminator loss: 0.799220
Generator loss: 1.355704
===============
Epoch 2 out of 2
Iteration 2540
Discriminator loss: 1.078027
Generator loss: 0.813071
===============
Epoch 2 out of 2
Iteration 2550
Discriminator loss: 1.033325
Generator loss: 0.807969
===============
Epoch 2 out of 2
Iteration 2560
Discriminator loss: 1.058336
Generator loss: 0.817255
===============
Epoch 2 out of 2
Iteration 2570
Discriminator loss: 0.953538
Generator loss: 0.944743
===============
Epoch 2 out of 2
Iteration 2580
Discriminator loss: 0.846981
Generator loss: 1.498263
===============
Epoch 2 out of 2
Iteration 2590
Discriminator loss: 0.867466
Generator loss: 1.844753
===============
Epoch 2 out of 2
Iteration 2600
Discriminator loss: 0.868803
Generator loss: 1.113406
===============
Epoch 2 out of 2
Iteration 2610
Discriminator loss: 1.068083
Generator loss: 1.672372
===============
Epoch 2 out of 2
Iteration 2620
Discriminator loss: 1.471784
Generator loss: 0.448744
===============
Epoch 2 out of 2
Iteration 2630
Discriminator loss: 1.226513
Generator loss: 0.670668
===============
Epoch 2 out of 2
Iteration 2640
Discriminator loss: 0.741024
Generator loss: 1.470922
===============
Epoch 2 out of 2
Iteration 2650
Discriminator loss: 1.023485
Generator loss: 1.143057
===============
Epoch 2 out of 2
Iteration 2660
Discriminator loss: 1.082412
Generator loss: 0.879865
===============
Epoch 2 out of 2
Iteration 2670
Discriminator loss: 0.810366
Generator loss: 1.606004
===============
Epoch 2 out of 2
Iteration 2680
Discriminator loss: 0.835720
Generator loss: 1.538970
===============
Epoch 2 out of 2
Iteration 2690
Discriminator loss: 0.797141
Generator loss: 1.216795
===============
Epoch 2 out of 2
Iteration 2700
Discriminator loss: 1.017424
Generator loss: 2.996279
===============
Epoch 2 out of 2
Iteration 2710
Discriminator loss: 0.677505
Generator loss: 1.939396
===============
Epoch 2 out of 2
Iteration 2720
Discriminator loss: 0.836611
Generator loss: 1.200613
===============
Epoch 2 out of 2
Iteration 2730
Discriminator loss: 0.900360
Generator loss: 1.136622
===============
Epoch 2 out of 2
Iteration 2740
Discriminator loss: 0.828774
Generator loss: 1.358834
===============
Epoch 2 out of 2
Iteration 2750
Discriminator loss: 0.969649
Generator loss: 0.966951
===============
Epoch 2 out of 2
Iteration 2760
Discriminator loss: 0.664686
Generator loss: 1.876929
===============
Epoch 2 out of 2
Iteration 2770
Discriminator loss: 1.059785
Generator loss: 0.792947
===============
Epoch 2 out of 2
Iteration 2780
Discriminator loss: 0.990705
Generator loss: 0.918419
===============
Epoch 2 out of 2
Iteration 2790
Discriminator loss: 0.936173
Generator loss: 0.952065
===============
Epoch 2 out of 2
Iteration 2800
Discriminator loss: 1.183332
Generator loss: 0.666686
===============
Epoch 2 out of 2
Iteration 2810
Discriminator loss: 0.804094
Generator loss: 1.373822
===============
Epoch 2 out of 2
Iteration 2820
Discriminator loss: 0.754696
Generator loss: 1.440413
===============
Epoch 2 out of 2
Iteration 2830
Discriminator loss: 0.752520
Generator loss: 1.256199
===============
Epoch 2 out of 2
Iteration 2840
Discriminator loss: 0.661371
Generator loss: 1.613757
===============
Epoch 2 out of 2
Iteration 2850
Discriminator loss: 0.844643
Generator loss: 1.107434
===============
Epoch 2 out of 2
Iteration 2860
Discriminator loss: 1.803858
Generator loss: 3.096932
===============
Epoch 2 out of 2
Iteration 2870
Discriminator loss: 0.676424
Generator loss: 1.756718
===============
Epoch 2 out of 2
Iteration 2880
Discriminator loss: 1.079554
Generator loss: 0.816606
===============
Epoch 2 out of 2
Iteration 2890
Discriminator loss: 1.119600
Generator loss: 0.714314
===============
Epoch 2 out of 2
Iteration 2900
Discriminator loss: 0.726471
Generator loss: 1.507406
===============
Epoch 2 out of 2
Iteration 2910
Discriminator loss: 0.677075
Generator loss: 1.491076
===============
Epoch 2 out of 2
Iteration 2920
Discriminator loss: 0.777044
Generator loss: 1.260771
===============
Epoch 2 out of 2
Iteration 2930
Discriminator loss: 1.092294
Generator loss: 0.725297
===============
Epoch 2 out of 2
Iteration 2940
Discriminator loss: 0.708277
Generator loss: 1.725607
===============
Epoch 2 out of 2
Iteration 2950
Discriminator loss: 0.905654
Generator loss: 0.992040
===============
Epoch 2 out of 2
Iteration 2960
Discriminator loss: 1.211874
Generator loss: 0.609531
===============
Epoch 2 out of 2
Iteration 2970
Discriminator loss: 0.867176
Generator loss: 1.824099
===============
Epoch 2 out of 2
Iteration 2980
Discriminator loss: 0.903110
Generator loss: 1.925668
===============
Epoch 2 out of 2
Iteration 2990
Discriminator loss: 0.869704
Generator loss: 1.309639
===============
Epoch 2 out of 2
Iteration 3000
Discriminator loss: 1.089392
Generator loss: 0.826543
===============
Epoch 2 out of 2
Iteration 3010
Discriminator loss: 0.937937
Generator loss: 1.162990
===============
Epoch 2 out of 2
Iteration 3020
Discriminator loss: 1.036887
Generator loss: 0.818561
===============
Epoch 2 out of 2
Iteration 3030
Discriminator loss: 0.792260
Generator loss: 1.266539
===============
Epoch 2 out of 2
Iteration 3040
Discriminator loss: 0.869589
Generator loss: 1.806195
===============
Epoch 2 out of 2
Iteration 3050
Discriminator loss: 0.751717
Generator loss: 1.416737
===============
Epoch 2 out of 2
Iteration 3060
Discriminator loss: 1.084893
Generator loss: 0.775498
===============
Epoch 2 out of 2
Iteration 3070
Discriminator loss: 0.700596
Generator loss: 1.796428
===============
Epoch 2 out of 2
Iteration 3080
Discriminator loss: 0.878180
Generator loss: 1.006991
===============
Epoch 2 out of 2
Iteration 3090
Discriminator loss: 1.594646
Generator loss: 3.273612
===============
Epoch 2 out of 2
Iteration 3100
Discriminator loss: 1.301720
Generator loss: 0.638467
===============
Epoch 2 out of 2
Iteration 3110
Discriminator loss: 0.818361
Generator loss: 1.233299
===============
Epoch 2 out of 2
Iteration 3120
Discriminator loss: 0.908632
Generator loss: 1.059055
===============
Epoch 2 out of 2
Iteration 3130
Discriminator loss: 0.944600
Generator loss: 0.994642
===============
Epoch 2 out of 2
Iteration 3140
Discriminator loss: 1.017880
Generator loss: 0.853283
===============
Epoch 2 out of 2
Iteration 3150
Discriminator loss: 0.850172
Generator loss: 1.103059
===============
Epoch 2 out of 2
Iteration 3160
Discriminator loss: 0.754947
Generator loss: 1.623251
===============
Epoch 2 out of 2
Iteration 3170
Discriminator loss: 1.193186
Generator loss: 0.662508
===============
Epoch 2 out of 2
Iteration 3180
Discriminator loss: 1.103690
Generator loss: 0.817748
===============
Epoch 2 out of 2
Iteration 3190
Discriminator loss: 1.341816
Generator loss: 0.584588
===============
Epoch 2 out of 2
Iteration 3200
Discriminator loss: 0.678527
Generator loss: 1.678051
===============
Epoch 2 out of 2
Iteration 3210
Discriminator loss: 0.957475
Generator loss: 0.957283
===============
Epoch 2 out of 2
Iteration 3220
Discriminator loss: 0.840372
Generator loss: 1.182927
===============
Epoch 2 out of 2
Iteration 3230
Discriminator loss: 1.103657
Generator loss: 2.614297
===============
Epoch 2 out of 2
Iteration 3240
Discriminator loss: 0.966555
Generator loss: 0.999734
===============
Epoch 2 out of 2
Iteration 3250
Discriminator loss: 0.898444
Generator loss: 1.099698
===============
Epoch 2 out of 2
Iteration 3260
Discriminator loss: 0.765637
Generator loss: 1.207275
===============
Epoch 2 out of 2
Iteration 3270
Discriminator loss: 0.955969
Generator loss: 1.195200
===============
Epoch 2 out of 2
Iteration 3280
Discriminator loss: 0.772572
Generator loss: 1.397287
===============
Epoch 2 out of 2
Iteration 3290
Discriminator loss: 0.811194
Generator loss: 1.184921
===============
Epoch 2 out of 2
Iteration 3300
Discriminator loss: 0.745109
Generator loss: 1.316326
===============
Epoch 2 out of 2
Iteration 3310
Discriminator loss: 0.974129
Generator loss: 0.910972
===============
Epoch 2 out of 2
Iteration 3320
Discriminator loss: 0.877464
Generator loss: 1.110866
===============
Epoch 2 out of 2
Iteration 3330
Discriminator loss: 1.440299
Generator loss: 0.495371
===============
Epoch 2 out of 2
Iteration 3340
Discriminator loss: 1.279001
Generator loss: 0.600450
===============
Epoch 2 out of 2
Iteration 3350
Discriminator loss: 1.030310
Generator loss: 0.923065
===============
Epoch 2 out of 2
Iteration 3360
Discriminator loss: 0.768480
Generator loss: 1.543864
===============
Epoch 2 out of 2
Iteration 3370
Discriminator loss: 0.978426
Generator loss: 0.879116
===============
Epoch 2 out of 2
Iteration 3380
Discriminator loss: 0.813067
Generator loss: 1.274551
===============
Epoch 2 out of 2
Iteration 3390
Discriminator loss: 0.890242
Generator loss: 1.122586
===============
Epoch 2 out of 2
Iteration 3400
Discriminator loss: 1.079312
Generator loss: 0.866375
===============
Epoch 2 out of 2
Iteration 3410
Discriminator loss: 0.818272
Generator loss: 1.274089
===============
Epoch 2 out of 2
Iteration 3420
Discriminator loss: 1.513373
Generator loss: 0.545889
===============
Epoch 2 out of 2
Iteration 3430
Discriminator loss: 0.610937
Generator loss: 1.880644
===============
Epoch 2 out of 2
Iteration 3440
Discriminator loss: 0.860718
Generator loss: 1.123265
===============
Epoch 2 out of 2
Iteration 3450
Discriminator loss: 0.780856
Generator loss: 1.350305
===============
Epoch 2 out of 2
Iteration 3460
Discriminator loss: 0.962087
Generator loss: 0.897810
===============
Epoch 2 out of 2
Iteration 3470
Discriminator loss: 0.972518
Generator loss: 0.985038
===============
Epoch 2 out of 2
Iteration 3480
Discriminator loss: 0.771568
Generator loss: 1.304064
===============
Epoch 2 out of 2
Iteration 3490
Discriminator loss: 0.851804
Generator loss: 1.260448
===============
Epoch 2 out of 2
Iteration 3500
Discriminator loss: 0.957308
Generator loss: 0.988087
===============
Epoch 2 out of 2
Iteration 3510
Discriminator loss: 1.066103
Generator loss: 0.935803
===============
Epoch 2 out of 2
Iteration 3520
Discriminator loss: 0.734818
Generator loss: 1.315937
===============
Epoch 2 out of 2
Iteration 3530
Discriminator loss: 1.007474
Generator loss: 0.946083
===============
Epoch 2 out of 2
Iteration 3540
Discriminator loss: 1.270074
Generator loss: 0.689645
===============
Epoch 2 out of 2
Iteration 3550
Discriminator loss: 1.046456
Generator loss: 0.911701
===============
Epoch 2 out of 2
Iteration 3560
Discriminator loss: 1.246024
Generator loss: 0.660761
===============
Epoch 2 out of 2
Iteration 3570
Discriminator loss: 0.714767
Generator loss: 1.359571
===============
Epoch 2 out of 2
Iteration 3580
Discriminator loss: 0.748853
Generator loss: 1.536255
===============
Epoch 2 out of 2
Iteration 3590
Discriminator loss: 0.646544
Generator loss: 1.865455
===============
Epoch 2 out of 2
Iteration 3600
Discriminator loss: 0.687320
Generator loss: 1.456910
===============
Epoch 2 out of 2
Iteration 3610
Discriminator loss: 0.934922
Generator loss: 0.977021
===============
Epoch 2 out of 2
Iteration 3620
Discriminator loss: 0.664989
Generator loss: 1.556051
===============
Epoch 2 out of 2
Iteration 3630
Discriminator loss: 1.060433
Generator loss: 0.839279
===============
Epoch 2 out of 2
Iteration 3640
Discriminator loss: 0.964181
Generator loss: 0.969463
===============
Epoch 2 out of 2
Iteration 3650
Discriminator loss: 0.662074
Generator loss: 1.493473
===============
Epoch 2 out of 2
Iteration 3660
Discriminator loss: 0.652898
Generator loss: 2.004190
===============
Epoch 2 out of 2
Iteration 3670
Discriminator loss: 1.204217
Generator loss: 0.656865
===============
Epoch 2 out of 2
Iteration 3680
Discriminator loss: 0.697303
Generator loss: 2.043005
===============
Epoch 2 out of 2
Iteration 3690
Discriminator loss: 1.291578
Generator loss: 0.603243
===============
Epoch 2 out of 2
Iteration 3700
Discriminator loss: 0.944522
Generator loss: 1.087492
===============
Epoch 2 out of 2
Iteration 3710
Discriminator loss: 0.699956
Generator loss: 1.649643
===============
Epoch 2 out of 2
Iteration 3720
Discriminator loss: 0.721869
Generator loss: 1.304482
===============
Epoch 2 out of 2
Iteration 3730
Discriminator loss: 0.666876
Generator loss: 1.605646
===============
Epoch 2 out of 2
Iteration 3740
Discriminator loss: 1.151505
Generator loss: 0.711419
===============
Epoch 2 out of 2
Iteration 3750
Discriminator loss: 0.807801
Generator loss: 1.276599
===============

CelebA

Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.

In [113]:
batch_size = 32
z_dim = 100
learning_rate = 0.0002
beta1 = 0.5

"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1

celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
          celeba_dataset.shape, celeba_dataset.image_mode)
Epoch 1 out of 1
Iteration 10
Discriminator loss: 0.585675
Generator loss: 1.928126
===============
Epoch 1 out of 1
Iteration 20
Discriminator loss: 0.567262
Generator loss: 1.850693
===============
Epoch 1 out of 1
Iteration 30
Discriminator loss: 0.697579
Generator loss: 1.561060
===============
Epoch 1 out of 1
Iteration 40
Discriminator loss: 0.545341
Generator loss: 2.253112
===============
Epoch 1 out of 1
Iteration 50
Discriminator loss: 0.549721
Generator loss: 3.253524
===============
Epoch 1 out of 1
Iteration 60
Discriminator loss: 0.951008
Generator loss: 1.004162
===============
Epoch 1 out of 1
Iteration 70
Discriminator loss: 1.464479
Generator loss: 0.524907
===============
Epoch 1 out of 1
Iteration 80
Discriminator loss: 0.547022
Generator loss: 2.993188
===============
Epoch 1 out of 1
Iteration 90
Discriminator loss: 1.786187
Generator loss: 4.920390
===============
Epoch 1 out of 1
Iteration 100
Discriminator loss: 1.044529
Generator loss: 0.909313
===============
Epoch 1 out of 1
Iteration 110
Discriminator loss: 1.373185
Generator loss: 0.565261
===============
Epoch 1 out of 1
Iteration 120
Discriminator loss: 0.556813
Generator loss: 2.036618
===============
Epoch 1 out of 1
Iteration 130
Discriminator loss: 1.735349
Generator loss: 0.394375
===============
Epoch 1 out of 1
Iteration 140
Discriminator loss: 0.414520
Generator loss: 3.490879
===============
Epoch 1 out of 1
Iteration 150
Discriminator loss: 0.608326
Generator loss: 3.386179
===============
Epoch 1 out of 1
Iteration 160
Discriminator loss: 0.954715
Generator loss: 2.887143
===============
Epoch 1 out of 1
Iteration 170
Discriminator loss: 0.856478
Generator loss: 1.160206
===============
Epoch 1 out of 1
Iteration 180
Discriminator loss: 1.062853
Generator loss: 0.917827
===============
Epoch 1 out of 1
Iteration 190
Discriminator loss: 0.556538
Generator loss: 2.012456
===============
Epoch 1 out of 1
Iteration 200
Discriminator loss: 1.027529
Generator loss: 4.466105
===============
Epoch 1 out of 1
Iteration 210
Discriminator loss: 0.533776
Generator loss: 2.511285
===============
Epoch 1 out of 1
Iteration 220
Discriminator loss: 0.764948
Generator loss: 1.230315
===============
Epoch 1 out of 1
Iteration 230
Discriminator loss: 0.754865
Generator loss: 1.602172
===============
Epoch 1 out of 1
Iteration 240
Discriminator loss: 0.989957
Generator loss: 0.978836
===============
Epoch 1 out of 1
Iteration 250
Discriminator loss: 1.329724
Generator loss: 0.588562
===============
Epoch 1 out of 1
Iteration 260
Discriminator loss: 0.448886
Generator loss: 3.181731
===============
Epoch 1 out of 1
Iteration 270
Discriminator loss: 1.456116
Generator loss: 0.540938
===============
Epoch 1 out of 1
Iteration 280
Discriminator loss: 0.820442
Generator loss: 1.400901
===============
Epoch 1 out of 1
Iteration 290
Discriminator loss: 0.993317
Generator loss: 1.278671
===============
Epoch 1 out of 1
Iteration 300
Discriminator loss: 0.752999
Generator loss: 1.598468
===============
Epoch 1 out of 1
Iteration 310
Discriminator loss: 0.688111
Generator loss: 1.734839
===============
Epoch 1 out of 1
Iteration 320
Discriminator loss: 0.769331
Generator loss: 1.319299
===============
Epoch 1 out of 1
Iteration 330
Discriminator loss: 0.595598
Generator loss: 3.860535
===============
Epoch 1 out of 1
Iteration 340
Discriminator loss: 0.766657
Generator loss: 3.142189
===============
Epoch 1 out of 1
Iteration 350
Discriminator loss: 1.255337
Generator loss: 0.668393
===============
Epoch 1 out of 1
Iteration 360
Discriminator loss: 0.637720
Generator loss: 2.708845
===============
Epoch 1 out of 1
Iteration 370
Discriminator loss: 0.894657
Generator loss: 1.257419
===============
Epoch 1 out of 1
Iteration 380
Discriminator loss: 3.075403
Generator loss: 0.089183
===============
Epoch 1 out of 1
Iteration 390
Discriminator loss: 0.884513
Generator loss: 4.697866
===============
Epoch 1 out of 1
Iteration 400
Discriminator loss: 0.783761
Generator loss: 1.254774
===============
Epoch 1 out of 1
Iteration 410
Discriminator loss: 1.771546
Generator loss: 0.371339
===============
Epoch 1 out of 1
Iteration 420
Discriminator loss: 0.881461
Generator loss: 2.541158
===============
Epoch 1 out of 1
Iteration 430
Discriminator loss: 1.672755
Generator loss: 0.399737
===============
Epoch 1 out of 1
Iteration 440
Discriminator loss: 1.212635
Generator loss: 0.818321
===============
Epoch 1 out of 1
Iteration 450
Discriminator loss: 1.225348
Generator loss: 0.663948
===============
Epoch 1 out of 1
Iteration 460
Discriminator loss: 1.418682
Generator loss: 2.657962
===============
Epoch 1 out of 1
Iteration 470
Discriminator loss: 1.677522
Generator loss: 2.106519
===============
Epoch 1 out of 1
Iteration 480
Discriminator loss: 0.486437
Generator loss: 2.580418
===============
Epoch 1 out of 1
Iteration 490
Discriminator loss: 1.787461
Generator loss: 0.326957
===============
Epoch 1 out of 1
Iteration 500
Discriminator loss: 1.209284
Generator loss: 1.629944
===============
Epoch 1 out of 1
Iteration 510
Discriminator loss: 0.844567
Generator loss: 2.714203
===============
Epoch 1 out of 1
Iteration 520
Discriminator loss: 1.037397
Generator loss: 1.074880
===============
Epoch 1 out of 1
Iteration 530
Discriminator loss: 0.803757
Generator loss: 2.494380
===============
Epoch 1 out of 1
Iteration 540
Discriminator loss: 0.822555
Generator loss: 1.116884
===============
Epoch 1 out of 1
Iteration 550
Discriminator loss: 0.897655
Generator loss: 1.121051
===============
Epoch 1 out of 1
Iteration 560
Discriminator loss: 1.417051
Generator loss: 2.165668
===============
Epoch 1 out of 1
Iteration 570
Discriminator loss: 0.579805
Generator loss: 2.521222
===============
Epoch 1 out of 1
Iteration 580
Discriminator loss: 1.119007
Generator loss: 1.349430
===============
Epoch 1 out of 1
Iteration 590
Discriminator loss: 1.011913
Generator loss: 1.028684
===============
Epoch 1 out of 1
Iteration 600
Discriminator loss: 0.787457
Generator loss: 1.822350
===============
Epoch 1 out of 1
Iteration 610
Discriminator loss: 0.782714
Generator loss: 1.231070
===============
Epoch 1 out of 1
Iteration 620
Discriminator loss: 0.561465
Generator loss: 1.913313
===============
Epoch 1 out of 1
Iteration 630
Discriminator loss: 0.667084
Generator loss: 1.705592
===============
Epoch 1 out of 1
Iteration 640
Discriminator loss: 0.960547
Generator loss: 2.276667
===============
Epoch 1 out of 1
Iteration 650
Discriminator loss: 0.769280
Generator loss: 1.503687
===============
Epoch 1 out of 1
Iteration 660
Discriminator loss: 0.847660
Generator loss: 1.330534
===============
Epoch 1 out of 1
Iteration 670
Discriminator loss: 0.698188
Generator loss: 1.378325
===============
Epoch 1 out of 1
Iteration 680
Discriminator loss: 0.764866
Generator loss: 1.363513
===============
Epoch 1 out of 1
Iteration 690
Discriminator loss: 1.998492
Generator loss: 0.252357
===============
Epoch 1 out of 1
Iteration 700
Discriminator loss: 1.071553
Generator loss: 1.053640
===============
Epoch 1 out of 1
Iteration 710
Discriminator loss: 0.672883
Generator loss: 1.581026
===============
Epoch 1 out of 1
Iteration 720
Discriminator loss: 0.695825
Generator loss: 1.450899
===============
Epoch 1 out of 1
Iteration 730
Discriminator loss: 0.876191
Generator loss: 1.210304
===============
Epoch 1 out of 1
Iteration 740
Discriminator loss: 0.616012
Generator loss: 1.933006
===============
Epoch 1 out of 1
Iteration 750
Discriminator loss: 1.062070
Generator loss: 0.899615
===============
Epoch 1 out of 1
Iteration 760
Discriminator loss: 0.759549
Generator loss: 1.632520
===============
Epoch 1 out of 1
Iteration 770
Discriminator loss: 0.894277
Generator loss: 3.599527
===============
Epoch 1 out of 1
Iteration 780
Discriminator loss: 1.114531
Generator loss: 0.822328
===============
Epoch 1 out of 1
Iteration 790
Discriminator loss: 0.564791
Generator loss: 4.299247
===============
Epoch 1 out of 1
Iteration 800
Discriminator loss: 1.231446
Generator loss: 0.720293
===============
Epoch 1 out of 1
Iteration 810
Discriminator loss: 0.729627
Generator loss: 2.188082
===============
Epoch 1 out of 1
Iteration 820
Discriminator loss: 0.525578
Generator loss: 2.465859
===============
Epoch 1 out of 1
Iteration 830
Discriminator loss: 0.594195
Generator loss: 2.271493
===============
Epoch 1 out of 1
Iteration 840
Discriminator loss: 0.871326
Generator loss: 1.230813
===============
Epoch 1 out of 1
Iteration 850
Discriminator loss: 0.784191
Generator loss: 1.444918
===============
Epoch 1 out of 1
Iteration 860
Discriminator loss: 1.266323
Generator loss: 2.370671
===============
Epoch 1 out of 1
Iteration 870
Discriminator loss: 2.778251
Generator loss: 0.111502
===============
Epoch 1 out of 1
Iteration 880
Discriminator loss: 1.100760
Generator loss: 0.746643
===============
Epoch 1 out of 1
Iteration 890
Discriminator loss: 0.758176
Generator loss: 4.594873
===============
Epoch 1 out of 1
Iteration 900
Discriminator loss: 1.142859
Generator loss: 0.689691
===============
Epoch 1 out of 1
Iteration 910
Discriminator loss: 0.890628
Generator loss: 1.226312
===============
Epoch 1 out of 1
Iteration 920
Discriminator loss: 1.088360
Generator loss: 0.768593
===============
Epoch 1 out of 1
Iteration 930
Discriminator loss: 0.849389
Generator loss: 3.824271
===============
Epoch 1 out of 1
Iteration 940
Discriminator loss: 0.897332
Generator loss: 2.657597
===============
Epoch 1 out of 1
Iteration 950
Discriminator loss: 1.045468
Generator loss: 0.849472
===============
Epoch 1 out of 1
Iteration 960
Discriminator loss: 0.971151
Generator loss: 1.509142
===============
Epoch 1 out of 1
Iteration 970
Discriminator loss: 2.106474
Generator loss: 0.232669
===============
Epoch 1 out of 1
Iteration 980
Discriminator loss: 1.120748
Generator loss: 0.758032
===============
Epoch 1 out of 1
Iteration 990
Discriminator loss: 1.491256
Generator loss: 0.442886
===============
Epoch 1 out of 1
Iteration 1000
Discriminator loss: 0.963644
Generator loss: 1.033987
===============
Epoch 1 out of 1
Iteration 1010
Discriminator loss: 1.111893
Generator loss: 0.756308
===============
Epoch 1 out of 1
Iteration 1020
Discriminator loss: 1.699380
Generator loss: 0.380064
===============
Epoch 1 out of 1
Iteration 1030
Discriminator loss: 0.817121
Generator loss: 1.423789
===============
Epoch 1 out of 1
Iteration 1040
Discriminator loss: 1.004258
Generator loss: 0.838963
===============
Epoch 1 out of 1
Iteration 1050
Discriminator loss: 1.336720
Generator loss: 2.299499
===============
Epoch 1 out of 1
Iteration 1060
Discriminator loss: 1.070759
Generator loss: 0.781740
===============
Epoch 1 out of 1
Iteration 1070
Discriminator loss: 1.036530
Generator loss: 0.916608
===============
Epoch 1 out of 1
Iteration 1080
Discriminator loss: 0.834480
Generator loss: 1.032493
===============
Epoch 1 out of 1
Iteration 1090
Discriminator loss: 1.416783
Generator loss: 0.456624
===============
Epoch 1 out of 1
Iteration 1100
Discriminator loss: 0.909219
Generator loss: 1.060601
===============
Epoch 1 out of 1
Iteration 1110
Discriminator loss: 0.552408
Generator loss: 2.438947
===============
Epoch 1 out of 1
Iteration 1120
Discriminator loss: 0.693878
Generator loss: 1.618498
===============
Epoch 1 out of 1
Iteration 1130
Discriminator loss: 1.192620
Generator loss: 0.703911
===============
Epoch 1 out of 1
Iteration 1140
Discriminator loss: 1.545079
Generator loss: 0.394615
===============
Epoch 1 out of 1
Iteration 1150
Discriminator loss: 0.891128
Generator loss: 0.996260
===============
Epoch 1 out of 1
Iteration 1160
Discriminator loss: 0.553807
Generator loss: 3.183320
===============
Epoch 1 out of 1
Iteration 1170
Discriminator loss: 0.995243
Generator loss: 1.978986
===============
Epoch 1 out of 1
Iteration 1180
Discriminator loss: 0.847778
Generator loss: 1.491794
===============
Epoch 1 out of 1
Iteration 1190
Discriminator loss: 0.613039
Generator loss: 1.726951
===============
Epoch 1 out of 1
Iteration 1200
Discriminator loss: 0.381207
Generator loss: 3.621882
===============
Epoch 1 out of 1
Iteration 1210
Discriminator loss: 1.867220
Generator loss: 0.273725
===============
Epoch 1 out of 1
Iteration 1220
Discriminator loss: 0.884893
Generator loss: 1.150265
===============
Epoch 1 out of 1
Iteration 1230
Discriminator loss: 1.006214
Generator loss: 0.828158
===============
Epoch 1 out of 1
Iteration 1240
Discriminator loss: 0.716301
Generator loss: 1.532205
===============
Epoch 1 out of 1
Iteration 1250
Discriminator loss: 1.418147
Generator loss: 0.462098
===============
Epoch 1 out of 1
Iteration 1260
Discriminator loss: 1.024508
Generator loss: 1.015122
===============
Epoch 1 out of 1
Iteration 1270
Discriminator loss: 0.935650
Generator loss: 3.139360
===============
Epoch 1 out of 1
Iteration 1280
Discriminator loss: 0.953566
Generator loss: 1.027415
===============
Epoch 1 out of 1
Iteration 1290
Discriminator loss: 1.061143
Generator loss: 0.956469
===============
Epoch 1 out of 1
Iteration 1300
Discriminator loss: 1.274939
Generator loss: 0.653079
===============
Epoch 1 out of 1
Iteration 1310
Discriminator loss: 0.755687
Generator loss: 1.310923
===============
Epoch 1 out of 1
Iteration 1320
Discriminator loss: 0.746521
Generator loss: 1.542324
===============
Epoch 1 out of 1
Iteration 1330
Discriminator loss: 1.398142
Generator loss: 2.329388
===============
Epoch 1 out of 1
Iteration 1340
Discriminator loss: 0.637211
Generator loss: 2.617105
===============
Epoch 1 out of 1
Iteration 1350
Discriminator loss: 0.469754
Generator loss: 3.692536
===============
Epoch 1 out of 1
Iteration 1360
Discriminator loss: 1.589319
Generator loss: 0.933779
===============
Epoch 1 out of 1
Iteration 1370
Discriminator loss: 1.318549
Generator loss: 0.916999
===============
Epoch 1 out of 1
Iteration 1380
Discriminator loss: 0.868781
Generator loss: 1.107745
===============
Epoch 1 out of 1
Iteration 1390
Discriminator loss: 0.708031
Generator loss: 1.600365
===============
Epoch 1 out of 1
Iteration 1400
Discriminator loss: 1.119533
Generator loss: 0.700824
===============
Epoch 1 out of 1
Iteration 1410
Discriminator loss: 0.511360
Generator loss: 2.675767
===============
Epoch 1 out of 1
Iteration 1420
Discriminator loss: 1.212919
Generator loss: 1.018132
===============
Epoch 1 out of 1
Iteration 1430
Discriminator loss: 2.431484
Generator loss: 0.162134
===============
Epoch 1 out of 1
Iteration 1440
Discriminator loss: 0.694436
Generator loss: 1.632397
===============
Epoch 1 out of 1
Iteration 1450
Discriminator loss: 0.692159
Generator loss: 1.584464
===============
Epoch 1 out of 1
Iteration 1460
Discriminator loss: 1.207944
Generator loss: 1.861417
===============
Epoch 1 out of 1
Iteration 1470
Discriminator loss: 0.787055
Generator loss: 1.378368
===============
Epoch 1 out of 1
Iteration 1480
Discriminator loss: 1.339225
Generator loss: 0.909307
===============
Epoch 1 out of 1
Iteration 1490
Discriminator loss: 1.095169
Generator loss: 1.563181
===============
Epoch 1 out of 1
Iteration 1500
Discriminator loss: 1.098724
Generator loss: 0.711834
===============
Epoch 1 out of 1
Iteration 1510
Discriminator loss: 1.533334
Generator loss: 0.401969
===============
Epoch 1 out of 1
Iteration 1520
Discriminator loss: 0.777530
Generator loss: 1.369300
===============
Epoch 1 out of 1
Iteration 1530
Discriminator loss: 1.734496
Generator loss: 0.342066
===============
Epoch 1 out of 1
Iteration 1540
Discriminator loss: 0.724590
Generator loss: 1.369402
===============
Epoch 1 out of 1
Iteration 1550
Discriminator loss: 0.841585
Generator loss: 1.563478
===============
Epoch 1 out of 1
Iteration 1560
Discriminator loss: 0.493966
Generator loss: 2.575626
===============
Epoch 1 out of 1
Iteration 1570
Discriminator loss: 1.562231
Generator loss: 3.510608
===============
Epoch 1 out of 1
Iteration 1580
Discriminator loss: 0.889298
Generator loss: 4.475933
===============
Epoch 1 out of 1
Iteration 1590
Discriminator loss: 0.763888
Generator loss: 1.751296
===============
Epoch 1 out of 1
Iteration 1600
Discriminator loss: 0.751739
Generator loss: 2.406839
===============
Epoch 1 out of 1
Iteration 1610
Discriminator loss: 1.715870
Generator loss: 0.339244
===============
Epoch 1 out of 1
Iteration 1620
Discriminator loss: 1.022220
Generator loss: 0.952966
===============
Epoch 1 out of 1
Iteration 1630
Discriminator loss: 0.771020
Generator loss: 2.402503
===============
Epoch 1 out of 1
Iteration 1640
Discriminator loss: 0.717205
Generator loss: 1.836905
===============
Epoch 1 out of 1
Iteration 1650
Discriminator loss: 1.521818
Generator loss: 0.447701
===============
Epoch 1 out of 1
Iteration 1660
Discriminator loss: 1.413515
Generator loss: 0.703690
===============
Epoch 1 out of 1
Iteration 1670
Discriminator loss: 0.717169
Generator loss: 1.761756
===============
Epoch 1 out of 1
Iteration 1680
Discriminator loss: 1.178947
Generator loss: 0.643282
===============
Epoch 1 out of 1
Iteration 1690
Discriminator loss: 0.669581
Generator loss: 1.627438
===============
Epoch 1 out of 1
Iteration 1700
Discriminator loss: 0.819642
Generator loss: 2.100718
===============
Epoch 1 out of 1
Iteration 1710
Discriminator loss: 1.067539
Generator loss: 2.167097
===============
Epoch 1 out of 1
Iteration 1720
Discriminator loss: 1.016110
Generator loss: 0.877262
===============
Epoch 1 out of 1
Iteration 1730
Discriminator loss: 0.734071
Generator loss: 1.379475
===============
Epoch 1 out of 1
Iteration 1740
Discriminator loss: 1.984552
Generator loss: 0.248974
===============
Epoch 1 out of 1
Iteration 1750
Discriminator loss: 1.040531
Generator loss: 0.833173
===============
Epoch 1 out of 1
Iteration 1760
Discriminator loss: 1.275798
Generator loss: 0.619233
===============
Epoch 1 out of 1
Iteration 1770
Discriminator loss: 1.548479
Generator loss: 0.398423
===============
Epoch 1 out of 1
Iteration 1780
Discriminator loss: 1.213851
Generator loss: 1.323655
===============
Epoch 1 out of 1
Iteration 1790
Discriminator loss: 1.376798
Generator loss: 0.492993
===============
Epoch 1 out of 1
Iteration 1800
Discriminator loss: 1.218914
Generator loss: 0.610993
===============
Epoch 1 out of 1
Iteration 1810
Discriminator loss: 1.236846
Generator loss: 0.588988
===============
Epoch 1 out of 1
Iteration 1820
Discriminator loss: 1.362881
Generator loss: 0.552266
===============
Epoch 1 out of 1
Iteration 1830
Discriminator loss: 0.902316
Generator loss: 2.342153
===============
Epoch 1 out of 1
Iteration 1840
Discriminator loss: 0.456085
Generator loss: 3.119187
===============
Epoch 1 out of 1
Iteration 1850
Discriminator loss: 1.213261
Generator loss: 0.651646
===============
Epoch 1 out of 1
Iteration 1860
Discriminator loss: 2.020574
Generator loss: 0.244397
===============
Epoch 1 out of 1
Iteration 1870
Discriminator loss: 0.879727
Generator loss: 1.134910
===============
Epoch 1 out of 1
Iteration 1880
Discriminator loss: 1.328244
Generator loss: 0.543891
===============
Epoch 1 out of 1
Iteration 1890
Discriminator loss: 0.631518
Generator loss: 2.341327
===============
Epoch 1 out of 1
Iteration 1900
Discriminator loss: 2.765803
Generator loss: 0.108798
===============
Epoch 1 out of 1
Iteration 1910
Discriminator loss: 0.624196
Generator loss: 3.180770
===============
Epoch 1 out of 1
Iteration 1920
Discriminator loss: 0.457895
Generator loss: 3.319443
===============
Epoch 1 out of 1
Iteration 1930
Discriminator loss: 0.621273
Generator loss: 2.292356
===============
Epoch 1 out of 1
Iteration 1940
Discriminator loss: 0.888784
Generator loss: 1.081478
===============
Epoch 1 out of 1
Iteration 1950
Discriminator loss: 0.969722
Generator loss: 2.428050
===============
Epoch 1 out of 1
Iteration 1960
Discriminator loss: 1.635476
Generator loss: 0.357488
===============
Epoch 1 out of 1
Iteration 1970
Discriminator loss: 0.683628
Generator loss: 2.170187
===============
Epoch 1 out of 1
Iteration 1980
Discriminator loss: 0.778613
Generator loss: 2.188229
===============
Epoch 1 out of 1
Iteration 1990
Discriminator loss: 0.765776
Generator loss: 1.221813
===============
Epoch 1 out of 1
Iteration 2000
Discriminator loss: 1.796270
Generator loss: 0.298924
===============
Epoch 1 out of 1
Iteration 2010
Discriminator loss: 0.795351
Generator loss: 1.591959
===============
Epoch 1 out of 1
Iteration 2020
Discriminator loss: 0.946449
Generator loss: 1.237194
===============
Epoch 1 out of 1
Iteration 2030
Discriminator loss: 1.619962
Generator loss: 0.409419
===============
Epoch 1 out of 1
Iteration 2040
Discriminator loss: 1.399655
Generator loss: 0.520510
===============
Epoch 1 out of 1
Iteration 2050
Discriminator loss: 0.644974
Generator loss: 1.683167
===============
Epoch 1 out of 1
Iteration 2060
Discriminator loss: 1.386443
Generator loss: 0.547421
===============
Epoch 1 out of 1
Iteration 2070
Discriminator loss: 1.075533
Generator loss: 0.698919
===============
Epoch 1 out of 1
Iteration 2080
Discriminator loss: 0.803239
Generator loss: 3.699027
===============
Epoch 1 out of 1
Iteration 2090
Discriminator loss: 1.603064
Generator loss: 0.405354
===============
Epoch 1 out of 1
Iteration 2100
Discriminator loss: 1.370968
Generator loss: 0.608936
===============
Epoch 1 out of 1
Iteration 2110
Discriminator loss: 0.907099
Generator loss: 0.933712
===============
Epoch 1 out of 1
Iteration 2120
Discriminator loss: 0.887980
Generator loss: 1.168773
===============
Epoch 1 out of 1
Iteration 2130
Discriminator loss: 0.811414
Generator loss: 1.888292
===============
Epoch 1 out of 1
Iteration 2140
Discriminator loss: 0.500515
Generator loss: 2.216551
===============
Epoch 1 out of 1
Iteration 2150
Discriminator loss: 1.121055
Generator loss: 1.229535
===============
Epoch 1 out of 1
Iteration 2160
Discriminator loss: 0.762226
Generator loss: 1.436064
===============
Epoch 1 out of 1
Iteration 2170
Discriminator loss: 0.982618
Generator loss: 0.830576
===============
Epoch 1 out of 1
Iteration 2180
Discriminator loss: 0.770168
Generator loss: 1.552351
===============
Epoch 1 out of 1
Iteration 2190
Discriminator loss: 0.716884
Generator loss: 1.447990
===============
Epoch 1 out of 1
Iteration 2200
Discriminator loss: 1.225848
Generator loss: 1.540322
===============
Epoch 1 out of 1
Iteration 2210
Discriminator loss: 1.189088
Generator loss: 0.668500
===============
Epoch 1 out of 1
Iteration 2220
Discriminator loss: 0.610778
Generator loss: 1.646030
===============
Epoch 1 out of 1
Iteration 2230
Discriminator loss: 0.538554
Generator loss: 1.863296
===============
Epoch 1 out of 1
Iteration 2240
Discriminator loss: 1.060139
Generator loss: 1.106634
===============
Epoch 1 out of 1
Iteration 2250
Discriminator loss: 0.388141
Generator loss: 3.811821
===============
Epoch 1 out of 1
Iteration 2260
Discriminator loss: 1.220605
Generator loss: 0.672767
===============
Epoch 1 out of 1
Iteration 2270
Discriminator loss: 1.565514
Generator loss: 0.403055
===============
Epoch 1 out of 1
Iteration 2280
Discriminator loss: 1.471620
Generator loss: 0.659090
===============
Epoch 1 out of 1
Iteration 2290
Discriminator loss: 1.163135
Generator loss: 0.722117
===============
Epoch 1 out of 1
Iteration 2300
Discriminator loss: 1.510404
Generator loss: 0.441092
===============
Epoch 1 out of 1
Iteration 2310
Discriminator loss: 0.829929
Generator loss: 1.470339
===============
Epoch 1 out of 1
Iteration 2320
Discriminator loss: 1.113299
Generator loss: 1.436963
===============
Epoch 1 out of 1
Iteration 2330
Discriminator loss: 1.456616
Generator loss: 0.471479
===============
Epoch 1 out of 1
Iteration 2340
Discriminator loss: 1.317503
Generator loss: 0.604359
===============
Epoch 1 out of 1
Iteration 2350
Discriminator loss: 0.878983
Generator loss: 1.146492
===============
Epoch 1 out of 1
Iteration 2360
Discriminator loss: 1.186074
Generator loss: 0.844384
===============
Epoch 1 out of 1
Iteration 2370
Discriminator loss: 0.998486
Generator loss: 2.461546
===============
Epoch 1 out of 1
Iteration 2380
Discriminator loss: 0.786336
Generator loss: 1.912340
===============
Epoch 1 out of 1
Iteration 2390
Discriminator loss: 1.291322
Generator loss: 0.577439
===============
Epoch 1 out of 1
Iteration 2400
Discriminator loss: 1.241025
Generator loss: 0.946084
===============
Epoch 1 out of 1
Iteration 2410
Discriminator loss: 2.344743
Generator loss: 0.181295
===============
Epoch 1 out of 1
Iteration 2420
Discriminator loss: 1.032670
Generator loss: 2.535621
===============
Epoch 1 out of 1
Iteration 2430
Discriminator loss: 1.042262
Generator loss: 1.385193
===============
Epoch 1 out of 1
Iteration 2440
Discriminator loss: 1.485492
Generator loss: 0.478878
===============
Epoch 1 out of 1
Iteration 2450
Discriminator loss: 1.317802
Generator loss: 1.632218
===============
Epoch 1 out of 1
Iteration 2460
Discriminator loss: 0.770118
Generator loss: 2.531605
===============
Epoch 1 out of 1
Iteration 2470
Discriminator loss: 1.048360
Generator loss: 0.872708
===============
Epoch 1 out of 1
Iteration 2480
Discriminator loss: 1.995728
Generator loss: 0.245090
===============
Epoch 1 out of 1
Iteration 2490
Discriminator loss: 0.685664
Generator loss: 1.613636
===============
Epoch 1 out of 1
Iteration 2500
Discriminator loss: 0.730429
Generator loss: 2.198102
===============
Epoch 1 out of 1
Iteration 2510
Discriminator loss: 0.953288
Generator loss: 0.936136
===============
Epoch 1 out of 1
Iteration 2520
Discriminator loss: 0.646170
Generator loss: 2.496600
===============
Epoch 1 out of 1
Iteration 2530
Discriminator loss: 0.713696
Generator loss: 1.369101
===============
Epoch 1 out of 1
Iteration 2540
Discriminator loss: 0.821220
Generator loss: 1.231929
===============
Epoch 1 out of 1
Iteration 2550
Discriminator loss: 1.009208
Generator loss: 1.111543
===============
Epoch 1 out of 1
Iteration 2560
Discriminator loss: 0.853132
Generator loss: 1.460807
===============
Epoch 1 out of 1
Iteration 2570
Discriminator loss: 0.623568
Generator loss: 1.918658
===============
Epoch 1 out of 1
Iteration 2580
Discriminator loss: 1.070789
Generator loss: 0.749375
===============
Epoch 1 out of 1
Iteration 2590
Discriminator loss: 1.346538
Generator loss: 0.557783
===============
Epoch 1 out of 1
Iteration 2600
Discriminator loss: 0.751467
Generator loss: 1.287571
===============
Epoch 1 out of 1
Iteration 2610
Discriminator loss: 1.778003
Generator loss: 0.330368
===============
Epoch 1 out of 1
Iteration 2620
Discriminator loss: 0.804434
Generator loss: 1.607973
===============
Epoch 1 out of 1
Iteration 2630
Discriminator loss: 1.103906
Generator loss: 1.068530
===============
Epoch 1 out of 1
Iteration 2640
Discriminator loss: 0.891636
Generator loss: 1.130196
===============
Epoch 1 out of 1
Iteration 2650
Discriminator loss: 0.880665
Generator loss: 2.009279
===============
Epoch 1 out of 1
Iteration 2660
Discriminator loss: 1.114234
Generator loss: 0.825882
===============
Epoch 1 out of 1
Iteration 2670
Discriminator loss: 0.835034
Generator loss: 1.593427
===============
Epoch 1 out of 1
Iteration 2680
Discriminator loss: 0.654177
Generator loss: 2.463157
===============
Epoch 1 out of 1
Iteration 2690
Discriminator loss: 0.651529
Generator loss: 1.533042
===============
Epoch 1 out of 1
Iteration 2700
Discriminator loss: 1.477156
Generator loss: 0.594809
===============
Epoch 1 out of 1
Iteration 2710
Discriminator loss: 0.866669
Generator loss: 1.084291
===============
Epoch 1 out of 1
Iteration 2720
Discriminator loss: 1.172170
Generator loss: 1.359137
===============
Epoch 1 out of 1
Iteration 2730
Discriminator loss: 0.684263
Generator loss: 2.542347
===============
Epoch 1 out of 1
Iteration 2740
Discriminator loss: 1.130474
Generator loss: 0.843860
===============
Epoch 1 out of 1
Iteration 2750
Discriminator loss: 2.025527
Generator loss: 0.240431
===============
Epoch 1 out of 1
Iteration 2760
Discriminator loss: 1.108597
Generator loss: 0.780278
===============
Epoch 1 out of 1
Iteration 2770
Discriminator loss: 0.592776
Generator loss: 2.417219
===============
Epoch 1 out of 1
Iteration 2780
Discriminator loss: 1.393415
Generator loss: 0.518774
===============
Epoch 1 out of 1
Iteration 2790
Discriminator loss: 0.866449
Generator loss: 1.687946
===============
Epoch 1 out of 1
Iteration 2800
Discriminator loss: 1.070612
Generator loss: 1.981396
===============
Epoch 1 out of 1
Iteration 2810
Discriminator loss: 1.326825
Generator loss: 0.864251
===============
Epoch 1 out of 1
Iteration 2820
Discriminator loss: 0.695950
Generator loss: 2.016321
===============
Epoch 1 out of 1
Iteration 2830
Discriminator loss: 1.333422
Generator loss: 0.631610
===============
Epoch 1 out of 1
Iteration 2840
Discriminator loss: 1.333442
Generator loss: 0.605253
===============
Epoch 1 out of 1
Iteration 2850
Discriminator loss: 1.348720
Generator loss: 0.521283
===============
Epoch 1 out of 1
Iteration 2860
Discriminator loss: 0.860687
Generator loss: 1.092086
===============
Epoch 1 out of 1
Iteration 2870
Discriminator loss: 0.888648
Generator loss: 2.264448
===============
Epoch 1 out of 1
Iteration 2880
Discriminator loss: 1.360068
Generator loss: 0.529221
===============
Epoch 1 out of 1
Iteration 2890
Discriminator loss: 1.095836
Generator loss: 0.892909
===============
Epoch 1 out of 1
Iteration 2900
Discriminator loss: 0.836939
Generator loss: 1.341700
===============
Epoch 1 out of 1
Iteration 2910
Discriminator loss: 0.891330
Generator loss: 3.408826
===============
Epoch 1 out of 1
Iteration 2920
Discriminator loss: 0.739447
Generator loss: 1.479040
===============
Epoch 1 out of 1
Iteration 2930
Discriminator loss: 0.948451
Generator loss: 1.068024
===============
Epoch 1 out of 1
Iteration 2940
Discriminator loss: 1.454786
Generator loss: 0.463323
===============
Epoch 1 out of 1
Iteration 2950
Discriminator loss: 1.325428
Generator loss: 0.555763
===============
Epoch 1 out of 1
Iteration 2960
Discriminator loss: 0.826362
Generator loss: 1.447702
===============
Epoch 1 out of 1
Iteration 2970
Discriminator loss: 0.836976
Generator loss: 1.427057
===============
Epoch 1 out of 1
Iteration 2980
Discriminator loss: 0.772480
Generator loss: 2.212893
===============
Epoch 1 out of 1
Iteration 2990
Discriminator loss: 1.882317
Generator loss: 0.316263
===============
Epoch 1 out of 1
Iteration 3000
Discriminator loss: 1.339538
Generator loss: 0.578636
===============
Epoch 1 out of 1
Iteration 3010
Discriminator loss: 1.327634
Generator loss: 0.955623
===============
Epoch 1 out of 1
Iteration 3020
Discriminator loss: 1.377020
Generator loss: 0.552877
===============
Epoch 1 out of 1
Iteration 3030
Discriminator loss: 0.816922
Generator loss: 1.470220
===============
Epoch 1 out of 1
Iteration 3040
Discriminator loss: 1.214039
Generator loss: 0.669975
===============
Epoch 1 out of 1
Iteration 3050
Discriminator loss: 0.977728
Generator loss: 1.509303
===============
Epoch 1 out of 1
Iteration 3060
Discriminator loss: 1.483337
Generator loss: 0.460561
===============
Epoch 1 out of 1
Iteration 3070
Discriminator loss: 1.750987
Generator loss: 0.397573
===============
Epoch 1 out of 1
Iteration 3080
Discriminator loss: 1.558192
Generator loss: 0.391983
===============
Epoch 1 out of 1
Iteration 3090
Discriminator loss: 0.974444
Generator loss: 1.114921
===============
Epoch 1 out of 1
Iteration 3100
Discriminator loss: 1.625235
Generator loss: 0.429958
===============
Epoch 1 out of 1
Iteration 3110
Discriminator loss: 1.168385
Generator loss: 0.689733
===============
Epoch 1 out of 1
Iteration 3120
Discriminator loss: 0.922198
Generator loss: 1.055995
===============
Epoch 1 out of 1
Iteration 3130
Discriminator loss: 1.295012
Generator loss: 0.574040
===============
Epoch 1 out of 1
Iteration 3140
Discriminator loss: 0.848687
Generator loss: 1.198644
===============
Epoch 1 out of 1
Iteration 3150
Discriminator loss: 1.084963
Generator loss: 2.089177
===============
Epoch 1 out of 1
Iteration 3160
Discriminator loss: 1.287107
Generator loss: 0.861526
===============
Epoch 1 out of 1
Iteration 3170
Discriminator loss: 0.858177
Generator loss: 1.210465
===============
Epoch 1 out of 1
Iteration 3180
Discriminator loss: 1.072590
Generator loss: 0.869219
===============
Epoch 1 out of 1
Iteration 3190
Discriminator loss: 1.618493
Generator loss: 0.388761
===============
Epoch 1 out of 1
Iteration 3200
Discriminator loss: 2.025095
Generator loss: 0.234490
===============
Epoch 1 out of 1
Iteration 3210
Discriminator loss: 1.266753
Generator loss: 0.707148
===============
Epoch 1 out of 1
Iteration 3220
Discriminator loss: 0.914710
Generator loss: 1.282067
===============
Epoch 1 out of 1
Iteration 3230
Discriminator loss: 1.116236
Generator loss: 0.760661
===============
Epoch 1 out of 1
Iteration 3240
Discriminator loss: 1.449063
Generator loss: 0.568416
===============
Epoch 1 out of 1
Iteration 3250
Discriminator loss: 1.326316
Generator loss: 0.715101
===============
Epoch 1 out of 1
Iteration 3260
Discriminator loss: 0.928517
Generator loss: 1.092808
===============
Epoch 1 out of 1
Iteration 3270
Discriminator loss: 0.981920
Generator loss: 1.033059
===============
Epoch 1 out of 1
Iteration 3280
Discriminator loss: 0.550223
Generator loss: 2.034760
===============
Epoch 1 out of 1
Iteration 3290
Discriminator loss: 0.711957
Generator loss: 2.718818
===============
Epoch 1 out of 1
Iteration 3300
Discriminator loss: 1.465650
Generator loss: 0.461049
===============
Epoch 1 out of 1
Iteration 3310
Discriminator loss: 1.052224
Generator loss: 0.991202
===============
Epoch 1 out of 1
Iteration 3320
Discriminator loss: 0.838812
Generator loss: 1.105639
===============
Epoch 1 out of 1
Iteration 3330
Discriminator loss: 0.969884
Generator loss: 1.425332
===============
Epoch 1 out of 1
Iteration 3340
Discriminator loss: 1.137170
Generator loss: 0.677023
===============
Epoch 1 out of 1
Iteration 3350
Discriminator loss: 1.545609
Generator loss: 0.444143
===============
Epoch 1 out of 1
Iteration 3360
Discriminator loss: 1.403676
Generator loss: 0.511877
===============
Epoch 1 out of 1
Iteration 3370
Discriminator loss: 0.788990
Generator loss: 1.736200
===============
Epoch 1 out of 1
Iteration 3380
Discriminator loss: 1.158241
Generator loss: 0.901930
===============
Epoch 1 out of 1
Iteration 3390
Discriminator loss: 1.208755
Generator loss: 0.765010
===============
Epoch 1 out of 1
Iteration 3400
Discriminator loss: 1.085099
Generator loss: 0.800215
===============
Epoch 1 out of 1
Iteration 3410
Discriminator loss: 1.190612
Generator loss: 0.895494
===============
Epoch 1 out of 1
Iteration 3420
Discriminator loss: 1.464297
Generator loss: 0.454605
===============
Epoch 1 out of 1
Iteration 3430
Discriminator loss: 1.353137
Generator loss: 0.521081
===============
Epoch 1 out of 1
Iteration 3440
Discriminator loss: 1.036273
Generator loss: 1.162946
===============
Epoch 1 out of 1
Iteration 3450
Discriminator loss: 1.419427
Generator loss: 0.554869
===============
Epoch 1 out of 1
Iteration 3460
Discriminator loss: 1.105955
Generator loss: 1.014806
===============
Epoch 1 out of 1
Iteration 3470
Discriminator loss: 0.838616
Generator loss: 1.137719
===============
Epoch 1 out of 1
Iteration 3480
Discriminator loss: 1.714237
Generator loss: 1.263464
===============
Epoch 1 out of 1
Iteration 3490
Discriminator loss: 0.840244
Generator loss: 1.356763
===============
Epoch 1 out of 1
Iteration 3500
Discriminator loss: 1.276390
Generator loss: 0.634105
===============
Epoch 1 out of 1
Iteration 3510
Discriminator loss: 1.339916
Generator loss: 0.569592
===============
Epoch 1 out of 1
Iteration 3520
Discriminator loss: 1.566278
Generator loss: 0.444318
===============
Epoch 1 out of 1
Iteration 3530
Discriminator loss: 1.703578
Generator loss: 0.359677
===============
Epoch 1 out of 1
Iteration 3540
Discriminator loss: 1.610600
Generator loss: 0.568536
===============
Epoch 1 out of 1
Iteration 3550
Discriminator loss: 1.386774
Generator loss: 0.617552
===============
Epoch 1 out of 1
Iteration 3560
Discriminator loss: 0.878191
Generator loss: 2.274899
===============
Epoch 1 out of 1
Iteration 3570
Discriminator loss: 1.171438
Generator loss: 0.821764
===============
Epoch 1 out of 1
Iteration 3580
Discriminator loss: 0.797152
Generator loss: 1.616295
===============
Epoch 1 out of 1
Iteration 3590
Discriminator loss: 1.259316
Generator loss: 1.311764
===============
Epoch 1 out of 1
Iteration 3600
Discriminator loss: 1.472491
Generator loss: 0.840164
===============
Epoch 1 out of 1
Iteration 3610
Discriminator loss: 1.098593
Generator loss: 1.150687
===============
Epoch 1 out of 1
Iteration 3620
Discriminator loss: 1.066497
Generator loss: 0.802684
===============
Epoch 1 out of 1
Iteration 3630
Discriminator loss: 1.390161
Generator loss: 0.593178
===============
Epoch 1 out of 1
Iteration 3640
Discriminator loss: 1.260956
Generator loss: 0.729190
===============
Epoch 1 out of 1
Iteration 3650
Discriminator loss: 0.681390
Generator loss: 2.134795
===============
Epoch 1 out of 1
Iteration 3660
Discriminator loss: 1.058209
Generator loss: 1.229002
===============
Epoch 1 out of 1
Iteration 3670
Discriminator loss: 0.978457
Generator loss: 1.117627
===============
Epoch 1 out of 1
Iteration 3680
Discriminator loss: 0.939838
Generator loss: 1.427837
===============
Epoch 1 out of 1
Iteration 3690
Discriminator loss: 1.308922
Generator loss: 0.579747
===============
Epoch 1 out of 1
Iteration 3700
Discriminator loss: 1.130865
Generator loss: 0.794204
===============
Epoch 1 out of 1
Iteration 3710
Discriminator loss: 0.927802
Generator loss: 1.481826
===============
Epoch 1 out of 1
Iteration 3720
Discriminator loss: 1.367091
Generator loss: 0.646081
===============
Epoch 1 out of 1
Iteration 3730
Discriminator loss: 1.278008
Generator loss: 0.631644
===============
Epoch 1 out of 1
Iteration 3740
Discriminator loss: 1.336217
Generator loss: 0.550869
===============
Epoch 1 out of 1
Iteration 3750
Discriminator loss: 1.678926
Generator loss: 0.375184
===============
Epoch 1 out of 1
Iteration 3760
Discriminator loss: 1.119079
Generator loss: 0.799628
===============
Epoch 1 out of 1
Iteration 3770
Discriminator loss: 1.280576
Generator loss: 0.734984
===============
Epoch 1 out of 1
Iteration 3780
Discriminator loss: 1.139456
Generator loss: 0.694444
===============
Epoch 1 out of 1
Iteration 3790
Discriminator loss: 1.095945
Generator loss: 1.080739
===============
Epoch 1 out of 1
Iteration 3800
Discriminator loss: 1.230117
Generator loss: 0.727188
===============
Epoch 1 out of 1
Iteration 3810
Discriminator loss: 1.272386
Generator loss: 0.627298
===============
Epoch 1 out of 1
Iteration 3820
Discriminator loss: 1.089679
Generator loss: 1.207983
===============
Epoch 1 out of 1
Iteration 3830
Discriminator loss: 1.875438
Generator loss: 0.311429
===============
Epoch 1 out of 1
Iteration 3840
Discriminator loss: 1.522350
Generator loss: 0.529727
===============
Epoch 1 out of 1
Iteration 3850
Discriminator loss: 1.624348
Generator loss: 0.490205
===============
Epoch 1 out of 1
Iteration 3860
Discriminator loss: 1.213734
Generator loss: 0.764344
===============
Epoch 1 out of 1
Iteration 3870
Discriminator loss: 0.961911
Generator loss: 1.024471
===============
Epoch 1 out of 1
Iteration 3880
Discriminator loss: 1.139441
Generator loss: 1.336762
===============
Epoch 1 out of 1
Iteration 3890
Discriminator loss: 1.423549
Generator loss: 0.524432
===============
Epoch 1 out of 1
Iteration 3900
Discriminator loss: 1.198473
Generator loss: 0.755432
===============
Epoch 1 out of 1
Iteration 3910
Discriminator loss: 1.470076
Generator loss: 0.551576
===============
Epoch 1 out of 1
Iteration 3920
Discriminator loss: 1.199552
Generator loss: 0.833495
===============
Epoch 1 out of 1
Iteration 3930
Discriminator loss: 0.936136
Generator loss: 1.166543
===============
Epoch 1 out of 1
Iteration 3940
Discriminator loss: 0.985868
Generator loss: 1.229933
===============
Epoch 1 out of 1
Iteration 3950
Discriminator loss: 0.975290
Generator loss: 1.005524
===============
Epoch 1 out of 1
Iteration 3960
Discriminator loss: 1.079247
Generator loss: 0.947627
===============
Epoch 1 out of 1
Iteration 3970
Discriminator loss: 1.043691
Generator loss: 0.945704
===============
Epoch 1 out of 1
Iteration 3980
Discriminator loss: 1.542832
Generator loss: 0.448992
===============
Epoch 1 out of 1
Iteration 3990
Discriminator loss: 1.510432
Generator loss: 0.487952
===============
Epoch 1 out of 1
Iteration 4000
Discriminator loss: 1.499580
Generator loss: 0.519971
===============
Epoch 1 out of 1
Iteration 4010
Discriminator loss: 1.126619
Generator loss: 0.833315
===============
Epoch 1 out of 1
Iteration 4020
Discriminator loss: 1.411680
Generator loss: 0.536150
===============
Epoch 1 out of 1
Iteration 4030
Discriminator loss: 1.231231
Generator loss: 0.724354
===============
Epoch 1 out of 1
Iteration 4040
Discriminator loss: 1.276494
Generator loss: 0.620077
===============
Epoch 1 out of 1
Iteration 4050
Discriminator loss: 0.987015
Generator loss: 1.067664
===============
Epoch 1 out of 1
Iteration 4060
Discriminator loss: 0.767491
Generator loss: 1.850105
===============
Epoch 1 out of 1
Iteration 4070
Discriminator loss: 1.216822
Generator loss: 0.773516
===============
Epoch 1 out of 1
Iteration 4080
Discriminator loss: 1.372189
Generator loss: 0.680738
===============
Epoch 1 out of 1
Iteration 4090
Discriminator loss: 1.047445
Generator loss: 0.865698
===============
Epoch 1 out of 1
Iteration 4100
Discriminator loss: 0.651674
Generator loss: 2.444908
===============
Epoch 1 out of 1
Iteration 4110
Discriminator loss: 1.368447
Generator loss: 0.669198
===============
Epoch 1 out of 1
Iteration 4120
Discriminator loss: 0.790162
Generator loss: 1.574084
===============
Epoch 1 out of 1
Iteration 4130
Discriminator loss: 1.473446
Generator loss: 0.811457
===============
Epoch 1 out of 1
Iteration 4140
Discriminator loss: 0.736892
Generator loss: 2.240633
===============
Epoch 1 out of 1
Iteration 4150
Discriminator loss: 1.080815
Generator loss: 0.801887
===============
Epoch 1 out of 1
Iteration 4160
Discriminator loss: 0.763114
Generator loss: 2.253479
===============
Epoch 1 out of 1
Iteration 4170
Discriminator loss: 1.059241
Generator loss: 0.805217
===============
Epoch 1 out of 1
Iteration 4180
Discriminator loss: 1.097593
Generator loss: 0.919562
===============
Epoch 1 out of 1
Iteration 4190
Discriminator loss: 2.031666
Generator loss: 0.280584
===============
Epoch 1 out of 1
Iteration 4200
Discriminator loss: 1.275702
Generator loss: 0.647769
===============
Epoch 1 out of 1
Iteration 4210
Discriminator loss: 1.418918
Generator loss: 0.692504
===============
Epoch 1 out of 1
Iteration 4220
Discriminator loss: 1.067249
Generator loss: 1.981938
===============
Epoch 1 out of 1
Iteration 4230
Discriminator loss: 0.906599
Generator loss: 0.959790
===============
Epoch 1 out of 1
Iteration 4240
Discriminator loss: 1.242242
Generator loss: 0.824000
===============
Epoch 1 out of 1
Iteration 4250
Discriminator loss: 1.084075
Generator loss: 0.904062
===============
Epoch 1 out of 1
Iteration 4260
Discriminator loss: 1.035481
Generator loss: 0.955414
===============
Epoch 1 out of 1
Iteration 4270
Discriminator loss: 1.260891
Generator loss: 0.682767
===============
Epoch 1 out of 1
Iteration 4280
Discriminator loss: 1.325710
Generator loss: 0.592934
===============
Epoch 1 out of 1
Iteration 4290
Discriminator loss: 0.694153
Generator loss: 1.969434
===============
Epoch 1 out of 1
Iteration 4300
Discriminator loss: 0.995227
Generator loss: 1.087027
===============
Epoch 1 out of 1
Iteration 4310
Discriminator loss: 1.221850
Generator loss: 0.696847
===============
Epoch 1 out of 1
Iteration 4320
Discriminator loss: 1.445161
Generator loss: 0.510839
===============
Epoch 1 out of 1
Iteration 4330
Discriminator loss: 1.503222
Generator loss: 0.469948
===============
Epoch 1 out of 1
Iteration 4340
Discriminator loss: 1.399531
Generator loss: 0.539026
===============
Epoch 1 out of 1
Iteration 4350
Discriminator loss: 1.296356
Generator loss: 0.793836
===============
Epoch 1 out of 1
Iteration 4360
Discriminator loss: 1.234578
Generator loss: 0.818462
===============
Epoch 1 out of 1
Iteration 4370
Discriminator loss: 1.057265
Generator loss: 1.144354
===============
Epoch 1 out of 1
Iteration 4380
Discriminator loss: 0.777391
Generator loss: 1.412241
===============
Epoch 1 out of 1
Iteration 4390
Discriminator loss: 1.646151
Generator loss: 0.378334
===============
Epoch 1 out of 1
Iteration 4400
Discriminator loss: 1.202635
Generator loss: 0.620749
===============
Epoch 1 out of 1
Iteration 4410
Discriminator loss: 1.160462
Generator loss: 0.789054
===============
Epoch 1 out of 1
Iteration 4420
Discriminator loss: 1.304034
Generator loss: 0.636539
===============
Epoch 1 out of 1
Iteration 4430
Discriminator loss: 1.171733
Generator loss: 0.686179
===============
Epoch 1 out of 1
Iteration 4440
Discriminator loss: 1.004320
Generator loss: 1.008644
===============
Epoch 1 out of 1
Iteration 4450
Discriminator loss: 0.938926
Generator loss: 1.154611
===============
Epoch 1 out of 1
Iteration 4460
Discriminator loss: 0.725252
Generator loss: 1.479921
===============
Epoch 1 out of 1
Iteration 4470
Discriminator loss: 1.188507
Generator loss: 0.958668
===============
Epoch 1 out of 1
Iteration 4480
Discriminator loss: 0.844811
Generator loss: 1.393249
===============
Epoch 1 out of 1
Iteration 4490
Discriminator loss: 1.420356
Generator loss: 0.604411
===============
Epoch 1 out of 1
Iteration 4500
Discriminator loss: 1.228870
Generator loss: 0.727120
===============
Epoch 1 out of 1
Iteration 4510
Discriminator loss: 1.149805
Generator loss: 0.762317
===============
Epoch 1 out of 1
Iteration 4520
Discriminator loss: 1.273344
Generator loss: 0.637461
===============
Epoch 1 out of 1
Iteration 4530
Discriminator loss: 1.204449
Generator loss: 0.740153
===============
Epoch 1 out of 1
Iteration 4540
Discriminator loss: 1.069050
Generator loss: 0.884810
===============
Epoch 1 out of 1
Iteration 4550
Discriminator loss: 0.720534
Generator loss: 1.440728
===============
Epoch 1 out of 1
Iteration 4560
Discriminator loss: 1.407796
Generator loss: 0.877018
===============
Epoch 1 out of 1
Iteration 4570
Discriminator loss: 1.538103
Generator loss: 0.421876
===============
Epoch 1 out of 1
Iteration 4580
Discriminator loss: 0.747292
Generator loss: 1.604206
===============
Epoch 1 out of 1
Iteration 4590
Discriminator loss: 0.970409
Generator loss: 0.988838
===============
Epoch 1 out of 1
Iteration 4600
Discriminator loss: 1.055768
Generator loss: 0.979692
===============
Epoch 1 out of 1
Iteration 4610
Discriminator loss: 0.921883
Generator loss: 1.218830
===============
Epoch 1 out of 1
Iteration 4620
Discriminator loss: 1.119241
Generator loss: 0.740130
===============
Epoch 1 out of 1
Iteration 4630
Discriminator loss: 1.590403
Generator loss: 0.394388
===============
Epoch 1 out of 1
Iteration 4640
Discriminator loss: 1.539512
Generator loss: 0.436174
===============
Epoch 1 out of 1
Iteration 4650
Discriminator loss: 1.495523
Generator loss: 0.482639
===============
Epoch 1 out of 1
Iteration 4660
Discriminator loss: 1.510167
Generator loss: 0.434291
===============
Epoch 1 out of 1
Iteration 4670
Discriminator loss: 0.793330
Generator loss: 1.629549
===============
Epoch 1 out of 1
Iteration 4680
Discriminator loss: 1.041768
Generator loss: 1.101968
===============
Epoch 1 out of 1
Iteration 4690
Discriminator loss: 1.515490
Generator loss: 0.479184
===============
Epoch 1 out of 1
Iteration 4700
Discriminator loss: 1.297388
Generator loss: 0.653721
===============
Epoch 1 out of 1
Iteration 4710
Discriminator loss: 1.281610
Generator loss: 0.718458
===============
Epoch 1 out of 1
Iteration 4720
Discriminator loss: 1.116582
Generator loss: 0.791684
===============
Epoch 1 out of 1
Iteration 4730
Discriminator loss: 1.387748
Generator loss: 0.546422
===============
Epoch 1 out of 1
Iteration 4740
Discriminator loss: 1.030280
Generator loss: 0.891068
===============
Epoch 1 out of 1
Iteration 4750
Discriminator loss: 1.547795
Generator loss: 0.418356
===============
Epoch 1 out of 1
Iteration 4760
Discriminator loss: 1.294658
Generator loss: 0.637312
===============
Epoch 1 out of 1
Iteration 4770
Discriminator loss: 1.532130
Generator loss: 0.536800
===============
Epoch 1 out of 1
Iteration 4780
Discriminator loss: 1.663078
Generator loss: 0.383423
===============
Epoch 1 out of 1
Iteration 4790
Discriminator loss: 1.244977
Generator loss: 0.701669
===============
Epoch 1 out of 1
Iteration 4800
Discriminator loss: 1.122488
Generator loss: 0.841159
===============
Epoch 1 out of 1
Iteration 4810
Discriminator loss: 1.094927
Generator loss: 0.851631
===============
Epoch 1 out of 1
Iteration 4820
Discriminator loss: 1.071899
Generator loss: 1.505388
===============
Epoch 1 out of 1
Iteration 4830
Discriminator loss: 0.843431
Generator loss: 1.196144
===============
Epoch 1 out of 1
Iteration 4840
Discriminator loss: 1.061904
Generator loss: 1.038040
===============
Epoch 1 out of 1
Iteration 4850
Discriminator loss: 1.559159
Generator loss: 0.505126
===============
Epoch 1 out of 1
Iteration 4860
Discriminator loss: 1.338018
Generator loss: 0.600458
===============
Epoch 1 out of 1
Iteration 4870
Discriminator loss: 1.228907
Generator loss: 0.775159
===============
Epoch 1 out of 1
Iteration 4880
Discriminator loss: 1.038544
Generator loss: 1.002353
===============
Epoch 1 out of 1
Iteration 4890
Discriminator loss: 0.672434
Generator loss: 2.073568
===============
Epoch 1 out of 1
Iteration 4900
Discriminator loss: 0.937641
Generator loss: 1.124220
===============
Epoch 1 out of 1
Iteration 4910
Discriminator loss: 1.124849
Generator loss: 0.730252
===============
Epoch 1 out of 1
Iteration 4920
Discriminator loss: 1.369472
Generator loss: 0.564615
===============
Epoch 1 out of 1
Iteration 4930
Discriminator loss: 1.367330
Generator loss: 0.583898
===============
Epoch 1 out of 1
Iteration 4940
Discriminator loss: 1.079560
Generator loss: 0.854875
===============
Epoch 1 out of 1
Iteration 4950
Discriminator loss: 0.902844
Generator loss: 1.093004
===============
Epoch 1 out of 1
Iteration 4960
Discriminator loss: 1.073164
Generator loss: 1.272130
===============
Epoch 1 out of 1
Iteration 4970
Discriminator loss: 1.253227
Generator loss: 0.772195
===============
Epoch 1 out of 1
Iteration 4980
Discriminator loss: 1.503930
Generator loss: 0.408739
===============
Epoch 1 out of 1
Iteration 4990
Discriminator loss: 1.235272
Generator loss: 0.715481
===============
Epoch 1 out of 1
Iteration 5000
Discriminator loss: 1.317949
Generator loss: 0.644794
===============
Epoch 1 out of 1
Iteration 5010
Discriminator loss: 1.657644
Generator loss: 0.401500
===============
Epoch 1 out of 1
Iteration 5020
Discriminator loss: 1.272664
Generator loss: 0.723536
===============
Epoch 1 out of 1
Iteration 5030
Discriminator loss: 1.158086
Generator loss: 0.945641
===============
Epoch 1 out of 1
Iteration 5040
Discriminator loss: 1.340300
Generator loss: 0.652887
===============
Epoch 1 out of 1
Iteration 5050
Discriminator loss: 1.064925
Generator loss: 1.523058
===============
Epoch 1 out of 1
Iteration 5060
Discriminator loss: 1.200751
Generator loss: 0.753723
===============
Epoch 1 out of 1
Iteration 5070
Discriminator loss: 1.308339
Generator loss: 0.613571
===============
Epoch 1 out of 1
Iteration 5080
Discriminator loss: 1.375861
Generator loss: 0.622725
===============
Epoch 1 out of 1
Iteration 5090
Discriminator loss: 0.940472
Generator loss: 1.166047
===============
Epoch 1 out of 1
Iteration 5100
Discriminator loss: 1.768898
Generator loss: 0.332029
===============
Epoch 1 out of 1
Iteration 5110
Discriminator loss: 1.547698
Generator loss: 0.528042
===============
Epoch 1 out of 1
Iteration 5120
Discriminator loss: 1.058760
Generator loss: 2.433580
===============
Epoch 1 out of 1
Iteration 5130
Discriminator loss: 1.516328
Generator loss: 0.521331
===============
Epoch 1 out of 1
Iteration 5140
Discriminator loss: 1.019326
Generator loss: 1.029936
===============
Epoch 1 out of 1
Iteration 5150
Discriminator loss: 1.198506
Generator loss: 0.821450
===============
Epoch 1 out of 1
Iteration 5160
Discriminator loss: 1.429779
Generator loss: 0.507175
===============
Epoch 1 out of 1
Iteration 5170
Discriminator loss: 1.527104
Generator loss: 0.499810
===============
Epoch 1 out of 1
Iteration 5180
Discriminator loss: 1.220140
Generator loss: 0.724967
===============
Epoch 1 out of 1
Iteration 5190
Discriminator loss: 2.183288
Generator loss: 0.208372
===============
Epoch 1 out of 1
Iteration 5200
Discriminator loss: 1.250660
Generator loss: 0.729857
===============
Epoch 1 out of 1
Iteration 5210
Discriminator loss: 1.155612
Generator loss: 0.816577
===============
Epoch 1 out of 1
Iteration 5220
Discriminator loss: 1.187008
Generator loss: 0.972681
===============
Epoch 1 out of 1
Iteration 5230
Discriminator loss: 1.452003
Generator loss: 0.555670
===============
Epoch 1 out of 1
Iteration 5240
Discriminator loss: 1.617298
Generator loss: 0.385938
===============
Epoch 1 out of 1
Iteration 5250
Discriminator loss: 1.056287
Generator loss: 0.984189
===============
Epoch 1 out of 1
Iteration 5260
Discriminator loss: 1.198622
Generator loss: 0.693536
===============
Epoch 1 out of 1
Iteration 5270
Discriminator loss: 1.185377
Generator loss: 0.712130
===============
Epoch 1 out of 1
Iteration 5280
Discriminator loss: 0.962097
Generator loss: 1.065508
===============
Epoch 1 out of 1
Iteration 5290
Discriminator loss: 1.257860
Generator loss: 0.692920
===============
Epoch 1 out of 1
Iteration 5300
Discriminator loss: 0.799815
Generator loss: 1.371227
===============
Epoch 1 out of 1
Iteration 5310
Discriminator loss: 1.310873
Generator loss: 0.693908
===============
Epoch 1 out of 1
Iteration 5320
Discriminator loss: 1.006911
Generator loss: 0.899730
===============
Epoch 1 out of 1
Iteration 5330
Discriminator loss: 1.210136
Generator loss: 0.875590
===============
Epoch 1 out of 1
Iteration 5340
Discriminator loss: 0.999740
Generator loss: 1.449913
===============
Epoch 1 out of 1
Iteration 5350
Discriminator loss: 0.834588
Generator loss: 1.644547
===============
Epoch 1 out of 1
Iteration 5360
Discriminator loss: 1.223401
Generator loss: 0.744474
===============
Epoch 1 out of 1
Iteration 5370
Discriminator loss: 1.226337
Generator loss: 0.863720
===============
Epoch 1 out of 1
Iteration 5380
Discriminator loss: 1.378828
Generator loss: 0.595599
===============
Epoch 1 out of 1
Iteration 5390
Discriminator loss: 1.434493
Generator loss: 0.563024
===============
Epoch 1 out of 1
Iteration 5400
Discriminator loss: 1.007882
Generator loss: 1.014948
===============
Epoch 1 out of 1
Iteration 5410
Discriminator loss: 1.262788
Generator loss: 0.656258
===============
Epoch 1 out of 1
Iteration 5420
Discriminator loss: 1.304277
Generator loss: 0.978378
===============
Epoch 1 out of 1
Iteration 5430
Discriminator loss: 0.928330
Generator loss: 0.959031
===============
Epoch 1 out of 1
Iteration 5440
Discriminator loss: 1.099286
Generator loss: 0.868918
===============
Epoch 1 out of 1
Iteration 5450
Discriminator loss: 1.149912
Generator loss: 0.781673
===============
Epoch 1 out of 1
Iteration 5460
Discriminator loss: 1.142452
Generator loss: 0.778011
===============
Epoch 1 out of 1
Iteration 5470
Discriminator loss: 0.932150
Generator loss: 1.297690
===============
Epoch 1 out of 1
Iteration 5480
Discriminator loss: 1.098488
Generator loss: 1.096354
===============
Epoch 1 out of 1
Iteration 5490
Discriminator loss: 1.447725
Generator loss: 0.470866
===============
Epoch 1 out of 1
Iteration 5500
Discriminator loss: 1.760060
Generator loss: 0.329738
===============
Epoch 1 out of 1
Iteration 5510
Discriminator loss: 1.395306
Generator loss: 0.575461
===============
Epoch 1 out of 1
Iteration 5520
Discriminator loss: 1.478388
Generator loss: 0.482441
===============
Epoch 1 out of 1
Iteration 5530
Discriminator loss: 1.288844
Generator loss: 0.756687
===============
Epoch 1 out of 1
Iteration 5540
Discriminator loss: 1.737742
Generator loss: 0.397172
===============
Epoch 1 out of 1
Iteration 5550
Discriminator loss: 1.417283
Generator loss: 0.523048
===============
Epoch 1 out of 1
Iteration 5560
Discriminator loss: 1.469157
Generator loss: 0.558124
===============
Epoch 1 out of 1
Iteration 5570
Discriminator loss: 1.600873
Generator loss: 0.445190
===============
Epoch 1 out of 1
Iteration 5580
Discriminator loss: 1.202885
Generator loss: 0.732510
===============
Epoch 1 out of 1
Iteration 5590
Discriminator loss: 1.862231
Generator loss: 0.335085
===============
Epoch 1 out of 1
Iteration 5600
Discriminator loss: 1.299349
Generator loss: 0.949058
===============
Epoch 1 out of 1
Iteration 5610
Discriminator loss: 1.177663
Generator loss: 0.753886
===============
Epoch 1 out of 1
Iteration 5620
Discriminator loss: 1.206985
Generator loss: 0.724740
===============
Epoch 1 out of 1
Iteration 5630
Discriminator loss: 1.252365
Generator loss: 0.652636
===============
Epoch 1 out of 1
Iteration 5640
Discriminator loss: 0.870540
Generator loss: 1.193707
===============
Epoch 1 out of 1
Iteration 5650
Discriminator loss: 1.229259
Generator loss: 0.675960
===============
Epoch 1 out of 1
Iteration 5660
Discriminator loss: 1.214630
Generator loss: 0.957398
===============
Epoch 1 out of 1
Iteration 5670
Discriminator loss: 1.229855
Generator loss: 0.739096
===============
Epoch 1 out of 1
Iteration 5680
Discriminator loss: 1.202087
Generator loss: 1.003677
===============
Epoch 1 out of 1
Iteration 5690
Discriminator loss: 0.868928
Generator loss: 1.357809
===============
Epoch 1 out of 1
Iteration 5700
Discriminator loss: 1.324338
Generator loss: 0.676086
===============
Epoch 1 out of 1
Iteration 5710
Discriminator loss: 1.172614
Generator loss: 0.776899
===============
Epoch 1 out of 1
Iteration 5720
Discriminator loss: 1.084461
Generator loss: 0.926624
===============
Epoch 1 out of 1
Iteration 5730
Discriminator loss: 0.994109
Generator loss: 1.023915
===============
Epoch 1 out of 1
Iteration 5740
Discriminator loss: 1.605701
Generator loss: 0.576985
===============
Epoch 1 out of 1
Iteration 5750
Discriminator loss: 1.181886
Generator loss: 0.701487
===============
Epoch 1 out of 1
Iteration 5760
Discriminator loss: 1.342625
Generator loss: 0.563991
===============
Epoch 1 out of 1
Iteration 5770
Discriminator loss: 1.345664
Generator loss: 0.547011
===============
Epoch 1 out of 1
Iteration 5780
Discriminator loss: 1.545732
Generator loss: 0.511680
===============
Epoch 1 out of 1
Iteration 5790
Discriminator loss: 1.478941
Generator loss: 0.499892
===============
Epoch 1 out of 1
Iteration 5800
Discriminator loss: 1.600723
Generator loss: 0.397919
===============
Epoch 1 out of 1
Iteration 5810
Discriminator loss: 1.393529
Generator loss: 0.547982
===============
Epoch 1 out of 1
Iteration 5820
Discriminator loss: 1.324132
Generator loss: 0.668433
===============
Epoch 1 out of 1
Iteration 5830
Discriminator loss: 0.992118
Generator loss: 0.956896
===============
Epoch 1 out of 1
Iteration 5840
Discriminator loss: 1.619215
Generator loss: 0.384939
===============
Epoch 1 out of 1
Iteration 5850
Discriminator loss: 1.111209
Generator loss: 0.957455
===============
Epoch 1 out of 1
Iteration 5860
Discriminator loss: 1.280674
Generator loss: 0.750695
===============
Epoch 1 out of 1
Iteration 5870
Discriminator loss: 1.353500
Generator loss: 0.666745
===============
Epoch 1 out of 1
Iteration 5880
Discriminator loss: 0.948162
Generator loss: 1.089768
===============
Epoch 1 out of 1
Iteration 5890
Discriminator loss: 0.970817
Generator loss: 1.129879
===============
Epoch 1 out of 1
Iteration 5900
Discriminator loss: 1.200903
Generator loss: 0.703689
===============
Epoch 1 out of 1
Iteration 5910
Discriminator loss: 1.483263
Generator loss: 0.490449
===============
Epoch 1 out of 1
Iteration 5920
Discriminator loss: 1.606264
Generator loss: 0.400837
===============
Epoch 1 out of 1
Iteration 5930
Discriminator loss: 1.509874
Generator loss: 0.445940
===============
Epoch 1 out of 1
Iteration 5940
Discriminator loss: 1.202453
Generator loss: 0.683128
===============
Epoch 1 out of 1
Iteration 5950
Discriminator loss: 1.009258
Generator loss: 1.340398
===============
Epoch 1 out of 1
Iteration 5960
Discriminator loss: 1.340411
Generator loss: 0.645368
===============
Epoch 1 out of 1
Iteration 5970
Discriminator loss: 1.495716
Generator loss: 0.463951
===============
Epoch 1 out of 1
Iteration 5980
Discriminator loss: 1.486101
Generator loss: 0.481142
===============
Epoch 1 out of 1
Iteration 5990
Discriminator loss: 1.129487
Generator loss: 0.834458
===============
Epoch 1 out of 1
Iteration 6000
Discriminator loss: 1.188510
Generator loss: 0.895829
===============
Epoch 1 out of 1
Iteration 6010
Discriminator loss: 1.183811
Generator loss: 0.756246
===============
Epoch 1 out of 1
Iteration 6020
Discriminator loss: 1.249270
Generator loss: 0.647547
===============
Epoch 1 out of 1
Iteration 6030
Discriminator loss: 1.511030
Generator loss: 0.498366
===============
Epoch 1 out of 1
Iteration 6040
Discriminator loss: 1.312964
Generator loss: 0.648082
===============
Epoch 1 out of 1
Iteration 6050
Discriminator loss: 1.837160
Generator loss: 0.312283
===============
Epoch 1 out of 1
Iteration 6060
Discriminator loss: 1.237429
Generator loss: 0.689976
===============
Epoch 1 out of 1
Iteration 6070
Discriminator loss: 1.410270
Generator loss: 0.651199
===============
Epoch 1 out of 1
Iteration 6080
Discriminator loss: 1.211861
Generator loss: 0.760948
===============
Epoch 1 out of 1
Iteration 6090
Discriminator loss: 1.331368
Generator loss: 0.616975
===============
Epoch 1 out of 1
Iteration 6100
Discriminator loss: 1.147753
Generator loss: 0.874929
===============
Epoch 1 out of 1
Iteration 6110
Discriminator loss: 1.527271
Generator loss: 0.438946
===============
Epoch 1 out of 1
Iteration 6120
Discriminator loss: 1.076652
Generator loss: 0.816164
===============
Epoch 1 out of 1
Iteration 6130
Discriminator loss: 1.475356
Generator loss: 0.526636
===============
Epoch 1 out of 1
Iteration 6140
Discriminator loss: 1.401861
Generator loss: 0.651840
===============
Epoch 1 out of 1
Iteration 6150
Discriminator loss: 1.607428
Generator loss: 0.386400
===============
Epoch 1 out of 1
Iteration 6160
Discriminator loss: 1.148352
Generator loss: 0.851261
===============
Epoch 1 out of 1
Iteration 6170
Discriminator loss: 1.461845
Generator loss: 0.631091
===============
Epoch 1 out of 1
Iteration 6180
Discriminator loss: 1.660458
Generator loss: 0.369976
===============
Epoch 1 out of 1
Iteration 6190
Discriminator loss: 1.097369
Generator loss: 0.884354
===============
Epoch 1 out of 1
Iteration 6200
Discriminator loss: 1.059448
Generator loss: 1.034826
===============
Epoch 1 out of 1
Iteration 6210
Discriminator loss: 0.817662
Generator loss: 1.619685
===============
Epoch 1 out of 1
Iteration 6220
Discriminator loss: 1.292526
Generator loss: 0.656633
===============
Epoch 1 out of 1
Iteration 6230
Discriminator loss: 1.074398
Generator loss: 0.883473
===============
Epoch 1 out of 1
Iteration 6240
Discriminator loss: 1.501079
Generator loss: 0.470291
===============
Epoch 1 out of 1
Iteration 6250
Discriminator loss: 1.546608
Generator loss: 0.437102
===============
Epoch 1 out of 1
Iteration 6260
Discriminator loss: 1.032136
Generator loss: 1.067095
===============
Epoch 1 out of 1
Iteration 6270
Discriminator loss: 1.180277
Generator loss: 0.688317
===============
Epoch 1 out of 1
Iteration 6280
Discriminator loss: 1.316209
Generator loss: 0.657085
===============
Epoch 1 out of 1
Iteration 6290
Discriminator loss: 1.215738
Generator loss: 0.899038
===============
Epoch 1 out of 1
Iteration 6300
Discriminator loss: 1.138088
Generator loss: 0.911197
===============
Epoch 1 out of 1
Iteration 6310
Discriminator loss: 1.280992
Generator loss: 0.636387
===============
Epoch 1 out of 1
Iteration 6320
Discriminator loss: 1.477348
Generator loss: 0.535099
===============
Epoch 1 out of 1
Iteration 6330
Discriminator loss: 1.608710
Generator loss: 0.481982
===============

Submitting This Project

When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.